Search

Many countries face problems in monitoring plant problems and monitoring large environments, as until now, there is no accurate means of aerial monitoring through which concerned parties can benefit from watersheds, monitor large agricultural areas, and make wise environmental decisions regarding them. This paper describes a pioneering approach to develop smart agriculture using multimission drones equipped with dual cognitive modules (brains) that are powered by a machine learning (ML) framework. The first brain uses deep reinforcement learning (DRL) principles to enable autonomous flight, allowing drones to navigate complex agricultural terrain with agility and flexibility. The second brain is responsible for precise and crucial agricultural tasks: counting trees, detecting water locations, and observing and analyzing plants using the Faster R‐CNN algorithm. The system is linked with the ground station for control and command, as well as it includes an Internet of Things (IoT) infrastructure equipped with sensors that collect soil parameters, which then get sent via 5G Wi‐Fi. The dual architecture of the drones, combined with the ground‐level IoT system, creates a comprehensive framework that not only enhances agricultural technologies but also aligns with environmental conservation goals, embodying a paradigm shift towards a greener and more sustainable future. Obtained results show reasonable results with an accuracy rate of 98%. [ABSTRACT FROM AUTHOR]

The implementation of the strategy of rural revitalization is a major ministerial work made by the Nineteenth National Congress of the Communist Party of China and is the general grasp of contemporary agriculture, peasants, and rural work. In recent years, with the rapid development of remote sensing technology and deep learning technology, the demand for the technology for the classification of crops on satellite remote sensing images based on deep learning technology has increased in agricultural insurance and land survey. Therefore, this paper trains one, which is 85.9%–92.8%, the accuracy of corn classification is 77%–93%, and the accuracy of forest classification is 77%–87.6%. Subsequently, the overall accuracy of classifying all directories through the multi-temporal validation data set between May 2017 and October 2017 reached 92.6%. Such a multi-time combination method can be used for monthly, timely, and efficient iteration of agricultural insurance and crop yield estimation, which will be more accurate each time. These methods can also be further applied to the growth and change monitoring of large agricultural planting areas, adding bricks and tiles to China's agricultural remote sensing. If the countryside is to be revitalized, agriculture must develop rapidly at the same time, industries must flourish, ecology must be livable, rural customs must be civilized, and life must be prosperous. Modern agriculture is a comprehensive circulation system with high yield, high quality, low consumption, ecology, environmental protection, and high efficiency. The development of modern agriculture is inseparable from the industrialization of agriculture, the globalization of agriculture, the digitization of agriculture, the integration of agriculture, the adjustment of agricultural structure, and agricultural innovation. Only the continuous development of modern agriculture can make rural revitalization enter a new journey. [ABSTRACT FROM AUTHOR]

China has proposed two major measures to address the "three rural issues": the first is to abolish the agricultural tax, which has been in place for over 2000 years; the second is to propose the construction of a new socialist countryside, which would mark the end of the old era and the beginning of the new. As a result, this paper employs in-depth learning technology to enhance rural tourism development and the creation of a new socialist countryside. This paper investigates deep-learning-based rural tourism and the creation of a new socialist countryside. Because MSE and MAE reflect the prediction error score, the lower the value, the better the recommendation accuracy. The MSE value of the machine learning algorithm is 2.456, the MSE value of the data mining algorithm is 2.324, and the MSE value of the convolution neural network algorithm is 2.102, when the number reaches 80. It can be concluded that the convolution neural network algorithm proposed in this paper has the lowest MSE and MAE values of the three methods, implying that the convolution neural network algorithm is the best of the three. The use of the convolution neural network algorithm to implement the scientific concept of development and the construction of a new socialist countryside is an important part of creating a harmonious society that fully meets the central government's objectives and requirements for the construction of a new socialist countryside. [ABSTRACT FROM AUTHOR]

In order to improve the effect of agricultural economic risk forecast, this paper studies the agricultural economic risk forecast combined with data mining technology and builds an intelligent agricultural economic risk forecast system. Moreover, this paper employs a dynamic factor model to estimate common factors that drive changes in target topics. In order to construct a sentiment index that can reflect the overall operating situation of the macroeconomy, this paper improves the agricultural economic risk mining algorithm and standardizes the sentiment value corresponding to the target theme. In addition, this article analyzes the sentiment changes of its individual topics one by one in combination with the specific economic environment. The simulation study shows that the agricultural economic risk forecast system based on data mining technology proposed in this paper has a good effect. [ABSTRACT FROM AUTHOR]

Grass damage in the seedling corn field has always been an important factor affecting the growth and development of crops. The existence of grass not only compresses the living space of corn seedlings but also easily causes insect damage. Therefore, it is essential for weeding in the seedling corn field. The existing weeding methods usually use manual or chemical herbicide spraying, which is not only time-consuming and laborious but also inefficient. With the development of artificial intelligence and modern agricultural technology, the use of robots for field weeding has become an effective means, which has attracted more and more attention of researchers at home and abroad. Therefore, based on the full investigation of the development of relevant technologies at home and abroad, this paper carried out the research on the real-time target recognition and ranging method of field weeding robot and proposed a target recognition method of weeding corn at the seedling stage by using an intelligent sensor network and deep learning convolution neural network. Among them, the intelligent sensor is mainly used for target ranging and obstacle avoidance, and CNN is mainly used for target recognition. Taking the images of corn seedlings and weeds in the seedling stage under natural environmental conditions as samples, the migration training is carried out through the depth network model of the COCO data set, and the convolution features are shared by the CNN depth network model and Fast-CNN depth network model. VGG and ResNet feature extraction networks are compared. The experimental results show that the CNN depth network model based on this paper has obvious advantages in rape and weed target recognition. The target recognition accuracy of rape and weeds can reach 87.64%, and the recall rate can reach 80.23%. Compared with other models, it has obvious advantages, which proves the effectiveness of this model. [ABSTRACT FROM AUTHOR]

With the sustained and rapid development of the economy, the food consumption structure has changed correspondingly and the market of cold and fresh products has developed rapidly, which puts forward the matching of cold chain logistics. Under the background of the construction of the belt and road and the pilot-free trade zone, the organic integration of the fresh agricultural products market and industry in Hainan is facing opportunities and challenges. In particular, in-depth research on the design and planning of the entire logistics system has not been carried out and the research on the distribution vehicle routing problem is still in the initial stage. This paper combs the relevant policies of cold chain logistics development in Hainan province. Given the imperfect system, the lack of policy guarantee measures, and the lack of regionality of the policy objective system, this paper puts forward some suggestions for improvement. The effective inventory control model of Hainan fresh agricultural products under cold chain logistics is explored by using the inventory management theory and the related theory of system dynamics. The simulation is carried out by using Vensim software, which provides a reference for improving the status of cold chain logistics of fresh agricultural products in Hainan. By saving funds, the profits of cold and fresh products are increased and the market competitiveness is improved. [ABSTRACT FROM AUTHOR]

With the rapid development of agriculture, modern agriculture has achieved remarkable results. Agriculture is the foundation of China's national economy, and the Party Central Committee has always insisted on solving the "three rural issues" as the top priority of the work of the whole party. However, China's agricultural foundation is weak, and the problem of unbalanced supply and demand structure of agricultural products still exists in agricultural development. With the development of blockchain, the application basis in the agricultural value chain has been established. At present, the research on the application of agricultural value chain financing is still in progress, but it is still in the initial stage. The integration of agricultural finance blockchain is low, and there are a series of problems. Extending blockchain technology to the financial area of agricultural value chains can help overcome the information barriers to traditional agricultural value chain financing and improve access to information resources for traditional agricultural value chains. The high cost of these value chains and inadequate financial management mechanisms remove bottlenecks in financing agricultural development. In this paper, we study the operation model and revenue distribution model of agricultural value chains using blockchain, analyze examples, and finally identify the basic elements of agricultural value chain financing based on sectoral chain technology. It provides theoretical support for the financing decision and production decision of each member of the agricultural supply chain, and it is hoped that the content and conclusions of the study can provide methodological reference and theoretical guidance for agricultural supply chain enterprises. [ABSTRACT FROM AUTHOR]

With the continuous development of information technology, various industries continue to use information technology to promote industrial upgrading and optimize the industrial structure. Agricultural informatization, as the only way for future agricultural development, will become an inevitable direction for the rejuvenation of traditional industries. The proposal of the development concept of "Mass Entrepreneurship, Mass Innovation" marks that my country has gradually entered an innovative society, and the development of public services and service products will become a powerful guarantee for promoting the construction of the agricultural informatization industry chain. This paper starts from the application of cloud computing and 5G in agriculture, considers the impact of big data on agriculture, and combines the business requirements and functional requirements of agricultural social services. The design of agricultural socialization service platform is realized, and finally, the service effect of the platform is evaluated by neural network. The following is a summary of the work done in this paper: (1) The research background and significance of the development concept of agricultural informatization services are expounded. Finally, the research content and method of this paper are discussed. (2) The technical principle and optimization algorithm of BPNN are introduced, and the evaluation index of the service effect of agricultural information platform is designed. (3) Select the appropriate parameters to build the experimental model and then train it, then compare the experimental effects of the traditional BP algorithm and the optimized three algorithms, and comprehensively evaluate the LM-BP model with the best performance. [ABSTRACT FROM AUTHOR]

The main path of development credit funds in rural poverty alleviation in Y province is crucial. This paper studies the rural poverty alleviation work in extreme poverty areas in Yunnan and puts forward targeted and instructive policy suggestions for specific difficult areas. Research the relationship between credit resource allocation and rural poverty alleviation. The existing research is mainly based on the relationship between financial development and economic growth, income growth, income distribution, and, on the surface, the relationship between the scale of financial development and the efficiency of financial development and other indicators. The purpose is to put forward targeted measures and suggestions on the basis of theoretical research and model analysis to help the Yunnan banking industry support poverty alleviation. The results of the study show that there is a causal relationship between agriculture-related loans. [ABSTRACT FROM AUTHOR]

Winter wheat is one of the most important food products. Increasing food demand and limited land resources have forced the development of agricultural production to be more refined and efficient. The most important part of agricultural production is sowing. With the promotion of precision agriculture, precision seeding has become the main component of modern agricultural seeding technology system, and the adoption of precision seeding technology is an important means of large-scale production and cost saving and efficiency enhancement. However, the current sowing technology and sowing equipment cannot meet the requirements of wheat sowing accuracy. In this context, a differential perturbation particle swarm optimization (DPPSO) algorithm is proposed by embedding differential perturbation into particle swarm optimization, which shows fast convergence speed and good global performance. After that the DPPSO is used to optimize the convolutional neural network (CNN) to build an optimized CNN (DPPSO-CNN) model and applied to the field of crops fine sowing. Finally, the experimental results show that the proposed method not only has a faster convergence rate but also achieves better wheat seeding performance. The research of this paper an effectively improves the accuracy and uniformity of wheat seeding and lay a foundation for improving wheat yield per unit area and promotes the intelligent development of agriculture in the future. [ABSTRACT FROM AUTHOR]

In order to explore the role of agricultural genetic breeding technology in elm cultivation, this paper improves the big data technology. According to the test data verification requirements, based on the Monte Carlo idea, a TDSTI statistical test method is proposed, and a set of judgment criteria for the significance of spatio-temporal autocorrelation is given. Moreover, in order to make the observed variables of the time lag series have a clearer geographical significance, the obtained spatio-temporal weight matrix is subjected to row standardization. In addition, this paper combines big data technology and agricultural genetic breeding technology to study the cultivation of elm trees. Finally, this paper conducts a correlation analysis between the distance matrix generated by cluster analysis of leaf shape traits and the distance matrix generated by cluster analysis of SSR molecular markers. The research results show that agricultural genetic breeding technology can play an important role in the cultivation of elm. [ABSTRACT FROM AUTHOR]

The rapid development of Internet technology promotes the ecological renewal of traditional industries. China's 14th Five-Year Plan clearly proposes to vigorously develop the Internet industry. Farmers are still the mainstay of China's population, and "agriculture, rural areas, and farmers" have always been highly valued by the party and the state. However, the rural economy has always been a weak link in China's economy, and agricultural products often have problems such as increasing production but not increasing income, relying on the weather, and having difficulties in sales. The root causes are the slow development of rural areas, farmers' economic awareness and lack of economic information. The Internet has broken this existing situation with the idea of flat network, breaking through the restrictions of traditional agricultural products trading channels, enabling farmers to directly connect with the market, and effectively improving trading profits. Firstly, this paper points out the influence of the Internet on the global economy and industry and further summarizes the development of e-commerce. Then, the advantages and characteristics of e-commerce are explained, and the theoretical basis and present situation of e-commerce development of agricultural products in China are expounded. Finally, the paper puts forward the imagination of China's e-commerce system of agricultural products, focuses on accelerating the standardization and systematization of agricultural products, and puts forward some suggestions and measures for the ecological evolution guarantee of agricultural products e-commerce. This paper is a research on the integration of agricultural products and ecological construction of e-commerce under the background of "internet plus." It is aimed at offering suggestions and suggestions for promoting agricultural product sales and rural development and promoting rural economic development, which is of great help to China's poverty alleviation cause and an effective way to achieve common prosperity. [ABSTRACT FROM AUTHOR]

In this paper, an in-depth study and analysis of the ecological economy of fine agriculture are carried out using image detection methods of smart sensor networks. The analog signal output from the wireless sensor network is filtered and thresholder to convert into a digital signal to complete the sensor monitoring data preprocessing for digital information analysis. In this paper, with the objectives of good environmental adaptability, low power consumption, low cost, and standardization, the key technologies of wireless sensor networks for fine agriculture are studied, including network structure, networking method, node positioning method, data fusion method, rapid energy self-sufficiency, and energy-saving strategy, and the performance evaluation method of wireless sensor network system, IoT-oriented middleware design method, generic node software and hardware design method, and typical application system. Firstly, a convolutional layer is used instead of a fully connected layer, which makes the network more flexible in terms of input image requirements and enables the calculation of the target rice region. Not only will many complex operations be generated, but it will also limit the generalization ability of the model. Then, by introducing a flexible connection layer based on unit and optimizing the loss function of the network, a crop convolutional neural network (Crop-Net) is finally proposed for training and testing rice images at different growth stages to improve the detection accuracy. In this paper, a network quality of service goal-driven evaluation strategy and evaluation method for agricultural wireless sensor network systems is designed to provide a reference for the establishment of industry standards for wireless sensor network systems for fine agriculture. [ABSTRACT FROM AUTHOR]

In order to improve the operation effect of farmer cooperatives, this paper combines the intelligent data sampling technology to analyze the ecological circle operation mode of farmer cooperatives. Moreover, this paper strives to promote the ecosphere business model, accelerate regional development, build agricultural pastoral complex projects and in-depth study TI-ADC modeling, error estimation, mismatch compensation, and other technologies, and carry out engineering realization. In addition, this paper uses technology to analyze intelligent data and builds a system structure based on the actual needs of the farmer cooperative ecosphere management. Finally, this paper analyzes the structure and flow of the data processing layer. The test results show that the ecosystem business model of farmer cooperatives based on intelligent data sampling technology proposed in this paper has good results. [ABSTRACT FROM AUTHOR]

In the Internet era, traditional performance management has failed to satisfy the modern enterprise development; therefore, enterprises must achieve timely innovation and improvement of performance management. The application of performance management in state-owned firms promotes employee motivation and skill development, as well as the development of innovative thinking. Performance effect, therefore, on the role of management in the state-owned enterprise development is bigger, especially because of the influence of traditional human resources performance management mode. The further development of state-owned enterprise resource management work affected the operation and management of state-owned enterprises. Therefore, state-owned enterprises must further optimize the path of performance management, to achieve its fine development. In view of this, this paper deeply analyzes the problems existing in the current performance management of state-owned enterprises and puts forward optimization methods for the problems, aiming at providing help for the optimization of the performance management of state-owned enterprises. In essence, a value network is a value symbiosis system between firms that involves resource sharing, value cocreation, risk sharing, and benefit win-win situations. The formation and development of value network not only extremely change the industrial structure and mode of production, but also have an important impact on enterprise innovation mechanism. Enterprise innovation under the value network system has become the focus of academic and business circles. With the rapid development of machine learning and internet of things (IOT) technologies, as well as China's urbanization, China's agriculture is embracing new development opportunities. Using artificial intelligence (AI) technology to effectively mine agricultural big data and realize effective control and management of intelligent agriculture has become a research hotspot and difficulty. Based on recurrent neural network (RNN) and IOT technology, this paper proposes an enterprise network innovation performance management path optimization system. [ABSTRACT FROM AUTHOR]

In this paper, we consider the Vennia algorithm to conduct in-depth research and analysis on the traceability of dual-chain blockchain agricultural products' E-commerce information. This paper adds a collaborative verification module to the traceability system and carries out a detailed design of information storage, traceability consensus algorithm, and smart contract for agricultural products according to the characteristics of the agricultural products supply chain, among which the collaborative verification module adopts dynamic data storage technology; the ConsiderVinia consensus algorithm is improved by introducing the way of integral penalty mechanism to ensure the block data validity. After a comparative study of the features and differences of the three major blockchain technology platforms, this paper selects the super ledger to implement the agricultural traceability system based on blockchain technology, introduces the partitioning and credit mechanism into the ConsiderVinia algorithm, and elaborates the improvement process of the algorithm. The improved algorithm reduces the malicious behavior of nodes and maintains the system security through a credit mechanism while maintaining the consistency of blockchain. In the event of a transaction dispute, the third-party platform will determine the party at fault based on the transaction records and other evidence and make corresponding punishments and compensations. The experiment proves that the algorithm proposed in this paper can reduce the amount of network data transmission in the process of node consensus, which is better than the ConsiderVinia algorithm in terms of both throughput and latency, improves the consensus efficiency, and alleviates the communication bottleneck caused by the increase of users in blockchain applications, and the solution of applying the blockchain technology to the agricultural products traceability system is practical and feasible. The blockchain-based agricultural products information traceability system solves the problems of information asymmetry, difficult sharing, easy tampering, and storage centralization in the traditional IoT-based agricultural products traceability system and truly realizes the credible and reliable traceability of the whole chain of agricultural products information. The research content and results of this paper have certain theoretical and practical values. [ABSTRACT FROM AUTHOR]

The traditional offline marketing mode of agricultural products was relatively single and difficult to adapt to the effective communication between agricultural and commercial enterprises and customers under the new situation, while the coordination between online agricultural products marketing management and customers' consumption needs was not enough. Therefore, this paper puts forward the research on the construction of online agricultural product consumption demand analysis model based on data mining technology. Based on the supply-demand relationship between agricultural and commercial enterprises and consumers, this paper analyzed consumers and their demand behavior for agricultural products and gave an evaluation model of customers' consumption demand for agricultural products. Using data mining technology, this paper made a cluster analysis on the characteristics of consumer demand behavior and established the mapping relationship between agricultural products and consumer demand. Then, the online consumption demand prediction and analysis model of agricultural products was put forward. Finally, the performance of demand forecasting model based on data classification was analyzed. The empirical results showed that the model proposed in this paper can better predict and analyze the consumption demand behavior of online agricultural products and had certain feasibility and effectiveness. The online consumption demand analysis model proposed in this paper played a positive role in improving the marketing management level of agricultural products. [ABSTRACT FROM AUTHOR]

Wireless sensor network (WSN) can play an important role during precision agriculture production to promote the growth of the agricultural economy. The application of WSN in agricultural production can achieve precision agriculture. WSN has the biggest challenge of energy efficiency. This paper proposes a model to efficiently utilize the energy of sensor nodes in precision agriculture production. The proposed model provides a comprehensive analysis of the precision agriculture. The model focuses on the characteristics of WSN and expands its application in precision agriculture. In addition, this paper also puts forward some technical prospects to provide a good reference for comprehensively and effectively improving the overall development level of precision agriculture. The paper analyzes the applicability and limitations of the existing sensor networks used for agricultural production technology. The ZigBee and Lora wireless protocols are utilized to have the best power consumption and communication in short distance and long distance. Our proposed model also suggests improvement measures for the shortcomings of existing WSN in the context of energy efficiency to provide an information platform for WSN to play a better role in agricultural production. [ABSTRACT FROM AUTHOR]

With the rapid development of agricultural economy, people are paying more and more attention to how to apply high-efficiency technologies that save resources to improve agricultural production efficiency, so water-saving irrigation technology has gradually developed. China's agricultural irrigation technology is relatively backward. In addition to the inappropriate irrigation methods and irrigation systems, problems such as siltation, seepage, and frost heave damage in irrigation canals have seriously affected the durability and service life of the canals. The backward irrigation technology seriously restricts the development of agricultural water-saving irrigation. Compared with large irrigation channels, the fabricated reinforced concrete small irrigation channels studied in this paper are less prone to frost heave damage and infiltration problems, and have the advantages of standardized production, simple transportation and installation, and convenient maintenance. In order to study the durability issues such as the basic characteristics, frost heave damage, and service life of fabricated irrigation channels, this paper takes the channel concrete and the formed channel as the research objects, and discusses the research on the properties of the channel concrete through theoretical research, numerical analysis, experiments, and other methods. Strength properties, water penetration resistance, cyanide ion penetration resistance and frost resistance; simulate the seasonal frost heave failure process of the channel; finally, on the basis of the test data, the service life aims to explore the safety and applicability of the fabricated reinforced concrete irrigation channel during the design use period. [ABSTRACT FROM AUTHOR]

Mobile communication is the communication between mobile bodies and an important way of communication between mobile users and fixed users. Power control technology is one of the keys of mobile communication information technology. This technology mainly adopts the core technology of the CDMA system. Through the self-interference system, it overcomes the problem of the mobile communication network and improves the quality of mobile communication. In the early twenty-first century, the rapid development of mobile communication technology has made important contributions to communication services worldwide. Rural tourism is a type of holiday with the aim of tourism, using the countryside as a framework for wandering and wild behavior. In fact, rural tourism is a project that has emerged in recent years, aiming to promote the economic development of rural areas and provide economic support for rural revitalization. At present, rural tourism is an important direction of tourism development, but the characteristics of the countryside have been ignored, and a large number of homogenizations have appeared in the development of rural areas. The development of rural tourism should highly combine agriculture, farmers, and rural development, make tourism an important industry in rural communities, strive to develop the local characteristics of rural tourism, increase tourism revenue, and truly benefit farmers. The purpose of this paper is to study the innovative research on the new path of rural tourism development based on mobile communication. It is hoped that mobile communication technology will be used to analyze the development patterns of rural tourism in different regions and to explore new development paths. This article first describes the notion of rural tourism, makes a comparative analysis of the different development models of rural tourism at home and abroad around rural revitalization, and makes a corresponding discussion on China's rural tourism model. China's rural tourism includes city-based, scenic-based, historical and cultural-based, transportation-based, industrial economy-based, and folk-custom-based. This paper briefly introduces the main development process of mobile communication technology, analyzes the relationship between the current era of big data and mobile communication networks, and explores the importance of mobile communication technology at present. The experimental results of this paper show that in terms of income, tourists above 70,000 yuan account for 31.8%, and tourists below 20,000 yuan account for 8.7%, indicating that rural tourism is less affected by the annual income of tourists. Tourists with a single consumption of less than 500 yuan accounted for 8.2%, indicating that there are many types of rural tourism, and tourists can choose according to their own abilities. [ABSTRACT FROM AUTHOR]

The agricultural domain in developing countries is mostly dictated by archaic rules based on traditions and inherited practices. With the evolution of digitalization and technology, it seems essential to apply new technologies to the agricultural field. Among the technologies to be exploited in agriculture, we mention sensors, IoT, WSN, cloud, blockchain, etc. We talk about smart agriculture in this case. In this paper, we propose a platform secured by blockchain for monitoring and securing production. This platform uses IoT connected sensors to track and save data. Our system is used to monitor the production process of olive trees. The goal is to track everything that enters and leaves our olive tree production from fertilizers, insecticides, and fortifiers to olives, trimming etc. The blockchain via its decentralized system allow a secure, irreversible, and clear monitoring. A dashboard allow us to highlight the changes while facilitating the work of farmers. Our prototype will be embedded via a Raspberry Pi 4 platform. [ABSTRACT FROM AUTHOR]

The application of Internet of Things technology in cold chain transportation can greatly strengthen the monitoring of all aspects of cold chain logistics, so as to promote the progress of cold chain logistics industry. In order to study this aspect, this paper chooses the key link of the Internet of Things as a breakthrough. By analyzing various aspects of the transportation process, an Internet of Things middleware framework serving cold chain transportation tracking is designed. The main products of logistics cold chain transportation are fresh agricultural products, so in order to further make the research fit the actual situation, this paper collects the logistics data and information of agricultural products through investigation and combines the core technology of agricultural products logistics with the Internet and the key technology of cold chain transportation to process the obtained information. The analytic hierarchy process and fuzzy comprehensive evaluation method are used in this process. The processing results prove the validity and rationality of the established index system. The purpose of developing the international trade management system is to enable the company to optimize its international trade management process, reduce some tedious and inconvenient manual operations, make the recording and statistics of international trade information very simple, improve work efficiency, and satisfy the information needs of various departments to enable enterprises to minimize costs, thereby enabling enterprises to obtain better economic benefits. [ABSTRACT FROM AUTHOR]

With the rapid development of China itself, the supply chain system has become an effective tool to enhance economic competitiveness, and the intelligent supply chain system integrates innovative technologies such as the Internet, the Internet of Things, cloud computing, and big data into the industrial supply chain management. The ant colony algorithm shows super flexibility and robustness at the level of optimizing many combination problems; the intelligent supply chain architecture of agricultural products is essentially the rational allocation of resources, which is a dynamic combination of resources and tasks that combines a variety of combinations to select the most appropriate and optimal performance. In this paper, the architecture of the intelligent supply chain of agricultural products is studied in combination with the improved ant colony algorithm, and some improvement strategies are adopted to avoid falling into local optimization or local convergence in order to avoid falling into local optimization or local convergence. The improvements of the algorithm mainly include the following: improving the path search of individual ants, improving the pheromone update strategy, improving the selection probability, and improving the dynamic growth mechanism of ants. In this paper, the VRPTW mathematical model, the dataset TSPLIB, and the operation data of the intelligent supply chain of agricultural products are used for test verification; the results can be obtained by verifying the results of the experiment closer to the optimal solution, and the efficiency of the algorithm is significantly improved. Therefore, through the improvement and optimization of the ant colony algorithm, it is very suitable for solving and optimizing the intelligent supply chain system of agricultural products. [ABSTRACT FROM AUTHOR]

With the establishment and perfection of social market economy, China has made changes to the disadvantages of farmers' vocational education system, such as singleness, backward educational means, and backward levels. Compared to traditional forms of farming, problems related to lack of farming expertise, poor scientific and technological awareness, and weak labor skills are analyzed by applying big data mining technology to retrieve key issues in order to establish a professional education system. Data mining can meet the needs of farming knowledge and rapidly develop into an automatic information farming model, which is an effective way to maximize and enhance professional knowledge. The establishment of a professional education system will train most scientific research members and further enhance diversified labor productivity. The experimental summary of this paper is as follows: (1) the relevant data need to be predicted before and after, the predicted experimental data will effectively improve students' grades, which is beneficial to the development of practical teaching, and the pretreatment stage plays a substantial role. (2) Among the three algorithms, the adaptive function of genetic clustering algorithm is obviously better than the other two algorithms, and the adaptive curve is relatively stable. (3) The comprehensive assessment of the course divides students into three categories: poor students, medium students, and excellent students, among which poor students account for 30%, medium students account for 50%, and excellent students account for 20%. (4) The standardization of the education system has brought users a good learning mechanism, in which the teaching resources have been strengthened, and users have very high satisfaction with the evaluation of the whole system. [ABSTRACT FROM AUTHOR]

The "carbon peak and carbon neutral" emission target has set new requirements for the supply chain structure, exacerbated by the complexity and vulnerability of the agricultural sector and global supply chains after the COVID-19 outbreak. Under these circumstances, the resilience evaluation of the agricultural supply chain based on green transformation became an important subject. Based on this topic with outstanding problems, this paper evaluates the resilience level of the agricultural supply chain in northeast China with the goal of achieving the "double carbon" objective. By focusing on its resilience, we selected Heilongjiang, Jilin, and Liaoning provinces as research subjects and collected the agricultural supply chain-related data from 2010 to 2019. Based on the relationship between supply chain nodes and the operation system, an evaluation model containing three levels was established. The entropy weight method and TOWA operator were used to carry out secondary weighting on the evaluation system and time levels containing 12 indicators, following the evaluation of the resilience level of the agricultural supply chain in three static and dynamic dimensions using the grey correlation method. The results show that the importance of the evaluation level of "internode resilience level" has always been a priority during the decade. Therefore, it is pointed out that the resilience construction and green transformation of the agricultural supply chain should be strengthened and implemented from the following three aspects: strengthening agricultural modernization, optimizing supply chain operation, and the implementation and promotion of effective policies. [ABSTRACT FROM AUTHOR]

In order to explore the path of agricultural policy finance in the intelligent service of rural revitalization under the background of big data, this paper combines data mining technology for financial data processing and big data technology for rural revitalization data analysis. Moreover, this paper combines rural revitalization with agricultural policy-based financial smart services. In addition, with the support of data mining technology, this paper constructs a research system on the path of agricultural policy finance in smart services for rural revitalization based on big data technology. Finally, this paper analyzes the data from the National Statistical Yearbook. Through experimental research, it can be known that the system constructed in this paper has certain effects. Moreover, with the support of the data mining system, this paper conducts research on the path of agricultural policy finance in smart services for rural revitalization and puts forward some suggestions. [ABSTRACT FROM AUTHOR]

The prerequisite for the reasonable construction and successful implementation of the financial sharing center of the agricultural enterprise group is that the agricultural enterprise group must fully understand the financial sharing center, understand the steps and key points of its construction, and comprehensively design and re-engineer the business process. This paper combines the big data technology to construct the financial sharing center system of agricultural enterprise groups, combines the machine learning algorithm to improve the big data processing algorithm, and builds the intelligent financial sharing platform with the support of the improved algorithm, and builds the overall system architecture and operation process. After constructing the system, the performance verification and practical verification of this system are carried out through experimental research. From the research results, it can be seen that the system constructed in this paper has good data processing effects and data sharing effects, and has good security, which meets the financial sharing needs of agricultural enterprise groups. [ABSTRACT FROM AUTHOR]

This paper attempts to build a performance evaluation system for agricultural financial project expenditures to make the performance evaluation of financial support for agriculture more maneuverable and provide a reference for the management of agricultural funds. Moreover, this paper combines the intelligent big data technology to construct the agricultural financial fund performance evaluation system, and describes the characteristics of the relevance of geographic elements in the entire spatial region through global spatial autocorrelation. Simultaneously, this paper uses different spatial weight matrices to examine the rationality and robustness of the results. In addition, this paper introduces covariates and removes trends through regression methods. Further, taking into account the characteristics, scientificity and operability of agricultural financial funds, the dimensions and structure of the performance evaluation of agricultural financial expenditures are drawn up. Finally, this paper verifies the effectiveness of this method through case studies, and gives several targeted suggestions. [ABSTRACT FROM AUTHOR]

Agriculture is the basic industry of the national economy, and the transformation of agricultural economic growth mode is of great significance to ensure the supply of agricultural products and improve the quality of agricultural products. Therefore, it is the only way to solve this problem to change the way of agricultural economic growth through scientific and technological investment, industrial structure adjustment, and other methods. Based on the fuzzy comprehensive evaluation method, this paper analyzes various factors of agricultural economic development and establishes a multilevel fuzzy comprehensive evaluation model of the development status of agricultural economic system. The stochastic frontier production function model of the fuzzy control comprehensive model is applied to decompose the agricultural labor productivity, and the counterfactual thinking and distribution method are used to analyze the influence of these factors on the evolution of provincial agricultural labor productivity differences. The value inequality decomposition method measures the contribution of each factor to the provincial agricultural labor productivity difference as well as the contribution of exogenous explanatory variables to the provincial agricultural technical efficiency difference. It is concluded that the relative contribution rate of nonagricultural activities to the difference in agricultural technical efficiency is the largest, and the average relative contribution rate reaches 74%. The improvement of agricultural labor productivity cannot rely solely on the increase in the input of agricultural material factors, but should rely on science and technology. [ABSTRACT FROM AUTHOR]

In the era of Internet +, modern industry has developed rapidly, the network economy has promoted the great development of the industrial economy, and the traditional industrial economic statistics method has not been suitable for the development needs of modern enterprises. In today's society, it can be described as the era of big data, the use of big data technology for industrial economic statistics is needed for the development of industrial modernization, and it is also a new requirement for industrial economic statistics put forward by social development. With the wide application of Internet of Things, cloud computing, mobile Internet, remote sensing, and geographic information technology in the economic field, precise economic policies have gradually developed and matured. Especially for different industries in the regional economy, according to the big data in the region, the big data mining technology and analysis technology can be used to obtain the development situation and future trend of the industrial economy in a timely and effective manner. Applying big data technology to macrodecision of regional economic information is an effective way to make macrodecision of current economy. Based on this background, this paper proposes a macroeconomic decision-making method for regional industries based on big data technology. Using data mining technology, time series data analysis methods combined with artificial intelligence analysis, the development trend of regional industries is obtained, and then the development trend of the industry is obtained. Development makes macroeconomic decisions. Taking agriculture as an example, the most popular analysis of the price trend of a certain agricultural product provides an effective reference for the development strategy of this agricultural product. The results show that the method proposed in this paper can effectively apply big data technology to the macrodecision-making of regional industrial economy. And it has better promotion significance. [ABSTRACT FROM AUTHOR]

Aiming at the problem of massive data storage and transaction authority in the blockchain system in the data sharing transaction scenario, this paper proposes a blockchain system for the controllable sharing transaction of massive data. By designing the blockchain system model of the consortium chain and private chain, reconstructing the data structure of the block, and introducing the InterPlanetary File System (IPFS) technology, we adopt the off-chain storage method to solve the problem of high cost caused by too much data carried by the block. The isolation control of data resource transactions is realized by introducing identity authentication and channel mechanism, which meets the needs of different subjects for confidentiality of transaction data information. From the analysis results of cold chain logistics efficiency, in the five years from 2017 to 2021, the comprehensive cold chain logistics efficiency, pure technology cold chain logistics efficiency, and scale cold chain logistics efficiency of agricultural product cold chain logistics in a certain region have all reached above 0.9. The return to scale remains unchanged, and the cold chain logistics resources have been effectively allocated and reasonably utilized. The value of comprehensive cold chain logistics efficiency, pure technology cold chain logistics efficiency, and scale cold chain logistics efficiency in a certain month is less than 1, which means that the cold chain logistics efficiency is weak or ineffective. This shows that in these years, the infrastructure investment, cold chain technical support, and management level related to the cold chain logistics of agricultural products in a certain region need to be strengthened, and it is necessary to adjust the input-output structure and allocate resources reasonably. From 2018 to 2021, the total factor productivity of agricultural product cold chain logistics in a certain region is greater than 0.85, indicating that the level of total factor productivity is relatively high during this time period, and the increase in the efficiency of technical cold chain logistics is the main reason for the increase in total factor productivity. [ABSTRACT FROM AUTHOR]

The green development of the entire agricultural industry chain is not only an important way to enhance the competitiveness of agricultural products and promote the value-added of the agricultural industry but also an inevitable choice to improve the efficiency of resource utilization and ensure sustainable economic development from the perspective of the ecological environment. This paper defines the connotation and characteristics of the green development of the whole agricultural industry chain and deeply analyzes the development status, major challenges, and feasible paths of the whole agricultural industry chain in China. It has built a whole industry chain development model of "Internet + modern agriculture" and proposed a decentralized agricultural data management system based on the IoT to solve the problem of untraceable of traditional agricultural products and other data. The agricultural IoT system is designed with a unique blockchain double-chain structure, using the global hash chain and the mutual verification between the transaction chains in each partition. It proposes the PMCP protocol, which improves the performance of the system by producing blocks in parallel for several consensus groups in each consensus cycle. The experimental results show that the proposed model is queryable, traceable, and trustworthy for whole-life agricultural data, and the proposed model outperforms other schemes in terms of throughput and delay. [ABSTRACT FROM AUTHOR]

With the development and leap of artificial intelligence technology, more and more robots have penetrated into all walks of life. Today's agriculture is changing in the direction of modernization and automation. On the one hand, because of rising labor costs, it cannot afford to consume a large amount of labor for agricultural operations. On the other hand, the population is growing rapidly, and traditional agricultural production, picking, and other links have been unable to keep pace with the development of the times. Therefore, it is very necessary to use artificial intelligence technology to transform traditional agriculture. The purpose of this paper is to use artificial intelligence technology to plan, track, and optimize the displacement trajectory of the agricultural picking robot, so as to improve the working efficiency of the picking robot. In this paper, the neural network, the D-H modeling method of the manipulator, and the forward and reverse motion of the manipulator are explained and analyzed, and based on the relevant algorithms of neural network, the manipulator is modeled, and then the, forward and reverse motion of the manipulator is analyzed in detail, and the digital model of the picking robot is constructed. Then, the angle and motion speed of each joint of the robot are analyzed to reduce the motion trajectory error caused by friction and other factors. Then, the simulation experiment of the displacement trajectory tracking control is carried out, and the linear trajectory motion and the arc trajectory motion are deeply analyzed, and the axis error is greatly reduced after 6 iterations. Finally, the displacement trajectory is optimized. The optimized total movement time is shortened by 6.84 seconds, which enables the picking robot to not only ensure work efficiency but also accurately complete the planned displacement trajectory. After continuous experiments on the algorithm model and the picking robot, the actual trajectory of the picking robot at 0.7 seconds can be expected. The trajectories are completely coincident, indicating that the neural network plays a very important role in the trajectory research of picking robots. [ABSTRACT FROM AUTHOR]

China is a large agricultural country. With the development of industrial production, mechanized harvesting has become an inevitable development trend of agricultural material harvesting. In this paper, based on the latest technology of polycrystalline ferroelectric composite materials in the design of the shovel frame of the harvester's vibrating excavating shovel, the relevant theories of the polycrystalline ferroelectric composite material and the shovel frame of the harvester's vibrating excavating shovel are based on the literature. After understanding, the shovel frame structure of the vibrating excavating shovel of the harvester was designed, and the latest technology of polycrystalline ferroelectric composite material was introduced in the design of the shovel frame of the vibrating excavating shovel of the harvester to make the vibration system have better performance. The designed shovel frame structure is tested, and the test results show that the horizontal output force received by the shovel designed in this paper increases with the increase of speed and is minimized at 0.26 m/s. The vertical output force decreases first and then increases with the increase of speed. It is the smallest when the running speed is 0.39 m/s. The horizontal working resistance is always greater than the vertical working resistance, and it can be seen that the design of the shovel frame structure can be realized in actual work. [ABSTRACT FROM AUTHOR]

In this paper, the implementation of SmartFarm AgriTech is done using IoT and cloud computing. The current world population is 7.9 billion and supposed to reach 12 billion by 2050, and it is difficult to feed such population in the future. So, for feeding the entire population, the agriculture sector should be embedded with the latest technologies. People living in urban city will be covered with their work and day to day activities which makes it really difficult to travel the village and monitor their cultivation regularly. Without proper maintenance of farms, it is hard to get the desired results, so using the cloud computing, IOT, networking, and many other technologies, one can easily maintain and monitor the crops, weather, water, and spraying fertilizers whenever needed. This SmartFarm AgriTech System is designed using Raspberry Pi and Arduino as the main microcontrollers to control the various sensors, relay-switch, and motor. AWS and ThingSpeak are used to create server and APIs to collect and store the data through Internet or via a Local Area Network (LAN). In addition to that, a GUI (Graphical User Interface) application is also created to control and monitor the data coming from Raspberry Pi and Arduino board. [ABSTRACT FROM AUTHOR]

As a large agricultural country, the three rural areas have always been one of the key areas of concern for national economic development. Among them, agricultural products finance is not only related to the development of agricultural economy, but also related to the poverty alleviation and wealth of thousands of farmers. With the rapid development of big data, cloud computing, blockchain, and other financial technologies, it will be important to build a new model of agricultural products supply chain finance and a special agricultural products O2O cloud service platform by relying on new technologies. Therefore, this paper conducts a study on the operation of agricultural products e-commerce platform based on cloud computing. This paper firstly introduces the advantages and key technologies of cloud computing. Secondly, this paper constructs the revenue models of e-merchants, farmers, and leading enterprises under insurance and risk-sharing modes and analyzes the optimal decisions of e-merchants, farmers, and leading enterprises under each mode and the influencing factors of the optimal decisions, so as to provide a new way of thinking for the construction of agricultural supply chain finance mode. [ABSTRACT FROM AUTHOR]

With the continuous advancement of science and technology, the fields of national defense, astronomy, industry, agriculture, and so on often require real-time acquisition of voltage, current, temperature, pressure, flow, and other signals, and the real-time requirements for signal acquisition are getting higher and higher. The traditional temperature acquisition method is to use the single chip or DSP as the control core to design the temperature monitoring system. However, this method has certain defects and cannot meet many high-demand signal acquisition occasions. On the one hand, most functions of this system are realized by software, and the operation of software will occupy part of the system sampling time, thus reducing the system sampling rate; on the other hand, the logic of the system to complex peripheral circuits cannot be well controlled. And Field Programmable Gate Array (FPGA) has characteristics such as parallel processing, controllability, and processing speed; therefore, the signal acquisition system with FPGA as the control core can realize high-speed signal collection. This paper studies the signal acquisition based on FPGA. In the signal acquisition system, FPGA is the control core of the whole system, and the relevant function modules of the control system complete the signal acquisition task. The acquisition control module is mainly to control the channel selection switch and the A/D converter to work, that is, to generate the logic control signal of multichannel selection and the control sequence of A/D conversion, so as to complete the acquisition and control of the multichannel analog input signal. The FPGA-based signal acquisition control system has the characteristics of short development cycle, flexible design, low cost, and high reliability. FPGA is an ideal architecture for signal acquisition, and the FPGA-based signal acquisition technology has very broad application prospects. [ABSTRACT FROM AUTHOR]

In order to improve the effect of crop growth monitoring, this paper combines the Internet of Things technology to construct a crop growth monitoring system based on the agricultural Internet of Things technology. Moreover, this paper combines the fuzzy theory to process the data of the agricultural Internet of Things to reduce the uncertainty of the data processing of the agricultural Internet of Things. After improving the fuzzy algorithm, this paper builds an intelligent model, builds the system structure framework according to the actual needs of crop growth monitoring, sets up and analyzes the environmental parameters, and builds the crop growth monitoring system from multiple perspectives. Finally, after constructing the system structure of this paper, the performance of the system proposed in this paper is verified. From the test results, it can be seen that the crop growth monitoring system based on the agricultural Internet of Things proposed in this paper has a good effect. [ABSTRACT FROM AUTHOR]

With the advent of the information age in the 21st century, Internet technology has developed rapidly. With the development of agriculture, industry, and service industry, Internet technology has also achieved further innovation and cross-border integration. The rapid development of Internet technology has provided new ideas for poverty alleviation in poor areas of China and accelerated the speed of poverty alleviation in poor areas. Based on the assumption of China's industrial poverty alleviation and the analysis of the implementation center, this paper puts forward an evaluation method of industrial poverty alleviation effect based on the fuzzy comprehensive evaluation method, which is evaluated from three aspects: income structure, expenditure structure, and labor resources. Taking Wuxi County as an example, this paper discusses the combination of human capital theory and multidimensional poverty theory. The evaluation of poverty alleviation effectiveness includes four indicators (comprehensive analysis, evaluation system, policy implementation, poverty alleviation funds) and 21 secondary indicators. Fuzzy comprehensive evaluation is an objective, fair, and comprehensive evaluation of the overall level of poverty alleviation and development in Wuxi. The expert scoring method is used to calculate the weight of each index and determine the level of members and the industrial situation of China's industrial poverty alleviation. According to the scores of each evaluation index, the poor households in Wuxi County are very satisfied with the person in charge of help, the villager group, the way of helping, and the effect of helping. [ABSTRACT FROM AUTHOR]

Agricultural industrial clusters are the basis for the formation of regional brands of agricultural products and also an effective way to enhance the regional brand value and competitiveness of agricultural products. Based on the agricultural industry cluster, carry out regional brand building of agricultural products, emphasizing that the production of agricultural products from raw material bases to product sales in specific administrative areas, and even the collaborative production services of relevant agricultural technology research and development institutions are connected to the local network, establishing a regional first-class agricultural product brand. The brand grows with the development of regional production bases. Therefore, this paper is aimed at exploring the research on the promotion of green brand competitiveness of agricultural products based on the theory of agricultural industrial clusters, analyzing the internal connection between agricultural product agglomeration effect and brand competitiveness, and exploring its advantages and disadvantages. Using this strategy, this paper will use the research method of specific analysis of specific problems, design an analysis model construction experiment based on the influencing factors of agricultural industrial clusters, and draw experimental conclusions through the analysis and comparison of experimental data. Through theoretical innovation and exploration, a model for the rapid development of green agricultural product brands can be found. The results show that the use of questionnaires to explore the differences in the planting characteristics of green agricultural products in industrial clusters can account for 35% of the brand competitiveness, promote the rapid development of the brand, and enhance the technological innovation ability by 19%. Therefore, combined with the characteristics of the current era, with the help of the national agricultural aid policy, fully absorb the transformation, actively innovate, and improve the level of agricultural cultivation. Analyze different application difficulties, explore development prospects, give full play to the competitiveness of agricultural products, realize high-yield green crops, use these theories as a guide to innovate and integrate, provide valuable experience clusters for the wide application of agricultural industrialization, and achieve sustainable regional economic structure and ecological environment. [ABSTRACT FROM AUTHOR]

Traditional cold chain logistics has problems such as centralized data storage, low data reliability, easy data tampering, and difficulty in locating responsible persons, which leads to the inability to guarantee consumer rights. To solve these problems, a cold chain logistics traceability system is proposed for fresh agricultural products based on blockchain. Both alliance chain and private chain are used in the paper in order to ensure that the product traceability system not only has certain openness but also must contain enough privacy and security. Alliance chain is mainly used to query and share product traceability information. The private chain will be used to collect and store the product traceability information of each enterprise and then connected to the alliance chain via hash pointers. The proposed system is beneficial for reducing the burden of network transmission of alliance chain and improving the efficiency of consumer product data query. At the same time, the private chain ensures the security and privacy of enterprise product data, which not only has high data storage efficiency but also can meet the requirements of all participants for the traceability system. In the experimental part, the feasibility of this system is verified through simulation experiments, which provides a reference for the combination of blockchain technology and cold chain logistics traceability system. [ABSTRACT FROM AUTHOR]

Agriculture 4.0 is the usage of advanced technologies for ensuring sustainability and efficient use of resources in agriculture, which can be accepted one of the biggest challenges of mankind. With Agriculture 4.0 technologies, it is aimed to raise productivity, reduce waste and costs. To ensure that agriculture 4.0 technologies are adopted by farmers as soon as possible, the perspective and perception of farmers to these technologies should be analyzed firstly. For this purpose, we propose a decision‐making framework to measure farmers' view of Agriculture 4.0 technologies and to perform a prioritization study based on the perception of use among these technologies. Multicriteria decision analysis is also utilized to deal with all qualitative and quantitative factors in the decision process. Within the scope of this study, interval‐valued spherical fuzzy numbers are used to model the vagueness in the process in the best manner and to be able to reflect the uncertainty arising from the usage of linguistic variables in the decision process. The SWARA and MAIRCA multicriteria decision making (MCDM) methods, which have been used frequently in the literature and are applied very successfully in MCDM problems, have been firstly extended by spherical fuzzy sets (SFSs) and the advantages for these methods have been utilized within the framework of fuzzy logic. The proposed method allows decision‐makers to mirror their hesitations in decision‐making using a linguistic evaluation scale established upon interval‐valued SFSs. A comparative analysis based on the ordinary fuzzy sets is also performed for the obtained results and the clear superiority of the proposed approach is presented. In addition, the robustness of the model is tested with sensitivity analysis. After these analyzes it is obtained that this paper provides a unique perspective to the literature due to its originality in both the subject and adopted fuzzy methodology. [ABSTRACT FROM AUTHOR]

Information sharing is the premise of the stable operation and win-win cooperation of the dual-channel agricultural supply chain. To arouse the enthusiasm of information sharing, this paper studies the incentive mechanism of information sharing of dual-channel agricultural product supply chain. The invention problem-solving theory (TRIZ) is adopted to analyze the functional model, the key problems, and the available resources of a dual-channel agricultural supply chain information sharing system. By using the invention principles of the conflict resolution theory, such as separation, precompensation, and feedback, the point bank reward mechanism and the risk evaluation and control mechanism of information sharing are proposed. TRIZ theory provides a new research method and incentive measure for effectively mobilizing the enthusiasm of information sharing. [ABSTRACT FROM AUTHOR]

Precision agriculture (PA) is the next generation of a technological revolution in smart farming, where sensing technology is the core technological player. Energy-efficient data transmission in PA via sensing technology is possible only when additional security measures are synchronized. Nevertheless, security considerations often introduce additional overhead. Thus, it is necessary to develop an efficient mechanism to achieve an optimal trade-off between security and resource efficiency. The prime purpose of the proposed study is to introduce a lightweight communication protocol that can ensure an adequate balance between energy efficiency and maximum-security demands to benefit the success of PA. This paper proposes a synchronized framework where unique public-key encryption has been used, unlike any existing approach to facilitate the participation of legitimate on-field sensors in PA. On the other hand, an algorithm for energy efficiency where unique structural management of routing is discussed concerning aggregator nodes. In contrast, the security algorithm discusses a uniquely progressive and noniterative mechanism to perform secure data aggregation with a parallel validation technique. The proposed logic is scripted in MATLAB, considering a suitable PA environment where comparative assessment is carried out on a uniform testbed. The study outcome exhibited the effectiveness of the proposed scheme concerning better energy efficiency and higher resiliency from threats in contrast to existing schemes. [ABSTRACT FROM AUTHOR]

Agriculture is crucial in catering to the increasing demand for food and employment. Thus, adoption of novel technologies is important. Many scientists have developed different theories and models explaining the process of behavioral change relevant to adoption. They are either completely different, similar, or improvements of previously developed models. Therefore, compilation and summarization of these theories and models will support future studies and researchers. Thus, an analysis of literature on technology adoption was conducted. The review was prepared based on literature from various sources spanning around 50 years. The theories and models identified by different studies were compiled and analyzed in this review paper. Many theories and models in agricultural technology adoption such as transtheoretical model, theory of reasoned action, theory of interpersonal behavior, model for innovation-decision process, different versions of technology acceptance model, theory of planned behavior, theory of diffusion of innovation, task-technology fit, technology readiness, unified theory of acceptance and use of technology, expectancy livelihood model, social cognitive theory, and perceived characteristics of innovating theory were compiled. Each theory and model has its own uniqueness, which had explained different aspects of technology adoption process and factors determining the behavioral change. These theories and models included affecting factors such as technological, personal, social, and economical factors. In conclusion, it can be stated that, rather than having a single theory or a model, an integrated and amalgamated form will be more explanatory for technology adoption. [ABSTRACT FROM AUTHOR]

With the mutual promotion of Internet information technology and economic globalization, the information economy has gradually become the focus of national development, and digital governance technology has been deeply integrated into the entire process of agricultural production. Through the reintegration of agricultural information flow, capital flow, business flow, and logistics, the transformation of intelligent agricultural production, networked operations, electronic management, and informatization of services has become an inevitable choice for rural revitalization. The purpose of this paper is to carry out a series of researches on the crowd-sensing and mining push technology of agricultural big data according to the application characteristics of agricultural data in the process of perception acquisition, analysis, and service. Therefore, we propose and study effective ways to collect IoT in rural complex environments, and how to use complex Internet data to mine rural areas vertically and provide a database source of large-scale data about agricultural resources. Experiments show that, from 10% of the death of a node to 90% of the death of a node, AODV passes about 550 laps, ExOR passes about 350 laps, and MWOR passes through less than 100 laps. From the results, the AODV algorithm is poor because it does not solve the problem of energy balance between nodes, while the ExOR algorithm selects the chance path with the least number of jumps. [ABSTRACT FROM AUTHOR]

The scientific evaluation of agricultural informatization construction level has important theoretical and practical significance, especially with the development of "national rural informatization demonstration province construction pilot," and the establishment of a comprehensive evaluation of agricultural informatization results of the index system has become an urgent problem to develop China's agricultural informatization. This paper draws on relevant research results to build an index system for evaluating the performance of agricultural informatization in three dimensions: the external environment, the internal environment, and the operational effect of agricultural informatization, and the study uses SPSS software to conduct factor analysis and improve the constructed index system. Then the interval intuitionistic fuzzy mathematics is applied to construct the RAIM performance evaluation model, which is verified by Hunan Province, and on this basis, the improvement measures of rural agricultural information management construction are proposed. [ABSTRACT FROM AUTHOR]

In recent years, research has combined the connection of agricultural equipment to increase crop growth rates and lower planting costs by refining the entire planting process. IT-enabled agriculture has beneficial effects on this industry and is yet a source of debate in academic circles. Trending network technologies like WSN and IoT have never been easy to develop and use in agriculture. The growth rate was not increased using outdated, conventional methods and technologies. Additionally, the rapid population expansion cannot meet human demands and expectations. Survey Methodology. The existence of IoT in agriculture was investigated and reported in this review. The paper describes the different IoT-agriculture network protocols. This study clarifies how the Internet affects agriculture and its underlying mechanisms. It also discusses how the growth rate is boosted when both sectors work together. This study intends to explore a platform that offers an infrastructure to link devices using the network protocol used in agriculture. In this study, several contemporary network difficulties relating to agriculture are also covered. Conclusion. The results of this study can be used as a guide for creating particular network protocols for the agriculture industry. [ABSTRACT FROM AUTHOR]

The times are advancing, the Internet is constantly advancing, and there are many examples of the combination of technology and life. The way people buy agricultural products is no longer limited to the physical market, but is being transformed into an agricultural product e-commerce website to achieve digital transformation. So far, a large number of agricultural products have been collected on the agricultural product e-commerce website, they come from all over the country, and different types and different regional agricultural products have appeared. On the other hand, users are faced with a large number of commodities on the Internet. If they simply use search engines, consumers need to spend a lot of time to find the commodities they are interested in by browsing. Searching from the recommended ones greatly reduces the product set and optimizes the performance of the e-commerce platform. Therefore, the generation of the personalized recommendation system meets the needs of the market. This research will improve the related recommendation algorithm by improving the user similarity calculation method based on artificial intelligence technology, improve the execution efficiency and accuracy of the improved algorithm, and use related technologies to develop an agricultural product e-commerce recommendation system. It has important theoretical and practical significance to save users' browsing time, improve users' shopping experience, and speed up the construction of agricultural product e-commerce. [ABSTRACT FROM AUTHOR]

In order to analyze the intergenerational income mobility of urban and rural residents, this paper uses big data technology to study the intergenerational income mobility of urban and rural residents in China, constructs a corresponding model, and presents an interval type-2 fuzzy model based on the distributed integration method. The model constructs an initial interval type-2 fuzzy model through a distributed integration strategy and provides an optimization method for the parameters of the interval type-2 fuzzy model based on the least squares method, which is used to ensure the prediction performance of the model. The experimental study verifies that the big data technology can play an important role in the research on the intergenerational income of urban and rural residents in China. [ABSTRACT FROM AUTHOR]