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H. Malon et al. in their paper entitled "Application of Low-Cost Sensors for the Development of a Methodology to Design Front-End Loaders for Tractors" developed a methodology to design tractor front-end loaders with a view of obtaining their accurate design during the bucket loading process. Sensors and applications in agricultural and environmental monitoring have become more essential to (1) farming practices, (2) crop growth estimation, (3) environmental changes, (4) global and regional observations on the earth's environment, and (5) monitoring/environmental analysis. M. Li et al. in their paper entitled "Response Mechanism of Cotton Growth to Water and Nutrients under Drip Irrigation with Plastic Mulch in Southern Xinjiang" studied the effects of water and nutrient control measures on cotton plant height, stem diameter, biomass, seed yield, and soil moisture under an irrigated plastic mulch production system. [Extracted from the article]

With the problem of nuclear leakage being concerned by more and more industries, the research of coastal ecological environment monitoring has become more and more important. Therefore, it is necessary to study the current unsystematic coastal ecological environment monitoring and protection system. Aiming at the accuracy of feature fusion and representation of single short environment information, this paper compares the classification effects of the three fusion methods on four classifiers: logistic regression, SVM, random forest, and naive Bayes, to verify the effectiveness of LDA and DS model fusion and determine the consistency vector representation method of short environment information data. This paper collects and analyzes the coastal data in recent years using multisource information fusion decision-making. In this paper, DS (Dempster Shafer) evidence algorithm is used to collect the data of coastal salinization degree and air relative humidity, and then, the DS feature matching model is introduced to fuse the whole index system. The method in the article completes the standardized and standardized processing of monitoring data digital conversion, quality control, and data classification, forms interrelated four-dimensional spatiotemporal data, and establishes a distributed, object-oriented, Internet-oriented dynamic management real-time and delayed database. Finally, this paper carries out tree decision processing on the coastal ecological environment monitoring data of multisource information fusion, to achieve the extraction and intuitive analysis of special data, and puts forward targeted protection strategies for the coastal ecological environment according to the data results of the DS algorithm. The research shows that the number of indicators in multisource information fusion in this paper is 16, a total of 3251 data, 2866 meaningful information, and 1869 data including ecological cycle. These data are the results of the collection of multi-information data. Based on the multilevel nature of the existing marine environment three-dimensional monitoring system, the study established a comprehensive resource-guaranteed framework and divided it into four levels according to the level of the marine monitoring system: country, sea area, locality, and data access point. In specific analysis, the guarantee resources involved in each level are introduced. On the basis of in-depth analysis of the requirements of the marine environment three-dimensional monitoring system operation guarantee and the guarantee resource structure, the marine environment three-dimensional monitoring operation comprehensive guarantee system is described from the internal structure and the external connection. The DS algorithm extracts the status information resources of various marine environment three-dimensional monitoring systems, through the interaction of various subsystems, realizes the operation and maintenance of the monitoring system, and provides various technical supports such as system evaluation and failure analysis. After multisource information fusion and decision-making, it is obtained that the index equilibrium module in the DS algorithm in this paper is 0.52, the sensitivity is 0.68, and the independence is 0.42. Among them, the range of sensitivity is the largest. In the simulation results, the eco-economic coefficient can be increased from 12% to 36%. Therefore, using the method of multisource information fusion for quantitative index analysis can provide data support for coastal ecological environment detection, to establish a more perfect protection system. [ABSTRACT FROM AUTHOR]

Wireless sensor network technology is widely used in various modern scenarios, and various industries have higher and higher requirements for the performance indicators of wireless sensor networks. A reasonable and effective layout of wireless sensor networks is conducive to the monitoring of environmental quality, various transactions, and status and transmits a large number of sensing data to the data aggregation center for processing and analysis. However, the operation and development of traditional wireless sensor networks are extremely dependent on the energy supply of the network. When the corresponding supply energy is limited, the operation life of the corresponding wireless sensor network will be greatly reduced. Based on the above situation, this paper proposes a nonuniform clustering routing protocol optimization algorithm from the energy loss of cluster head and clustering form algorithm in wireless sensor networks. At the level of cluster head calculation in wireless sensor networks, firstly, based on the adaptive estimation clustering algorithm, the core density is used as the estimation element to calculate the cluster head radius of wireless sensor networks. At the same time, this paper creatively proposes a fuzzy logic algorithm to further solve the uncertainty of cluster head selection, integrate the residual energy of cluster head nodes, and finally complete the reasonable distribution of cluster heads and realize the balance of node energy consumption. In order to further reduce the algorithm overhead of transmission between cluster heads and realize energy optimization, an intercluster routing optimization algorithm based on the ant colony algorithm is proposed. The pheromone is updated and disturbed by introducing chaotic mapping to ensure the optimal solution of the algorithm, and the optimal path is selected from the perspective of energy dispersion coefficient and distance coefficient, so as to optimize the energy consumption between cluster heads. The experimental results show that compared with the traditional algorithm, the proposed nonuniform clustering routing protocol optimization algorithm prolongs the corresponding life cycle by 75% and reduces the total network energy consumption by about 20%. Therefore, the algorithm achieves the purpose of optimizing network energy consumption and prolonging network life to a certain extent and has certain practical value. [ABSTRACT FROM AUTHOR]

With the continuous improvement of people's demand for ecological environment quality, the research on ecological environment monitoring, analysis and evaluation had been paid more and more attention by relevant departments and personnel. Because the images collected by remote sensing technology were many and multi-source, the features extracted from remote sensing images using traditional methods had been difficult to meet the needs of related industry applications. Therefore, this paper made use of the advantages of PIE remote sensing image processing software in data analysis and processing, and put forward the research on ecological environment monitoring, analysis and evaluation methods. Firstly, on the basis of summarizing the concepts and related problems of ecological environment, this paper analyzed the processing methods of remote sensing data sources of ecological environment, and explained the evaluation standards and common methods of ecological environment. Secondly, the composition of PIE remote sensing image processing technology system and its application advantages were described, the common indicators and analysis methods of ecological environment monitoring were given, and the index system and model of ecological environment comprehensive evaluation were established. Finally, through the analysis of experimental cases, the results showed that the ecological environment monitoring analysis and evaluation method proposed in this paper was feasible. Compared with the traditional methods, the method proposed in this paper could objectively evaluate the ecological environment. This paper can not only provide support for the analysis and processing of remote sensing image data, but also provide an important reference for the application of remote sensing technology in the field of ecological environment. [ABSTRACT FROM AUTHOR]

In order to improve the real-time prevention and control effect of community security, this paper uses environmental monitoring as the background to design a ZigBee-based wireless sensor network scheme. The ZigBee nodes in the system are set as FFD nodes and have the ability of coordinator and the nodes are not connected with other networks, and a network is formed through a multinode system. Moreover, the proposed cluster routing protocol firstly determines the orientation of the cluster and determines the cluster head in the cluster according to the orientation information of the cluster so that the clusters in the network can be evenly distributed. In addition, the system in this paper is mainly monitored through the Internet of Things and data processing through big data. Therefore, this paper mainly analyzes the data mining, data transmission, and monitoring effect of the system, combined with the simulation software. Finally, through experiments, this paper verifies that the Internet of Things real-time monitoring technology proposed in this paper has a good application effect in community security prevention and control. [ABSTRACT FROM AUTHOR]

In order to improve the monitoring effect of building indoor environment, this paper carries out indoor environment simulation through 3D modeling, uses image processing technology to collect environmental monitoring data, and proposes a routing algorithm applied in this environment. Moreover, this paper introduces the energy consumption model of sensor nodes and the multi-attribute decision-making method and uses the multi-attribute decision-making to propose an adaptive energy balance routing algorithm based on the indoor environment of the building. In addition, this paper establishes a simulation analysis, compares it with several other routing algorithms, and verifies that the proposed algorithm has better balance in network energy consumption and longer network life cycle. Finally, this paper combines three-dimensional modeling and image processing technology to construct the building indoor environment monitoring system. It can be seen from the simulation experiments that the proposed building indoor environment monitoring system based on 3D modeling and image processing can meet the actual needs of intelligent building indoor monitoring. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has affected people's lives in all aspects. This pandemic has raised the usage of ubiquitous networks such as mobile ad hoc networks (MANETs) for information exchange in various domains. MANET is a group of versatile nodes that communicates with each other without relying on a fixed physical framework. One of the prominent features of MANET is its versatile topology. Because of this striking feature, MANETs are employed in various domains like defense and combat operations, disaster management, healthcare, and environmental monitoring. In this paper, we enlighten the significance of MANET in the smart healthcare system. The COVID-19 pandemic outbreak demanded the reshaping of the healthcare systems to combat the pandemic and similar cataclysms. Existing healthcare systems are proved inefficient in dealing with pandemic situations, because they are not fully automated and also vulnerable to various security attacks. Therefore, it is vital to empower the healthcare sectors by integrating ubiquitous networks and other emerging technologies. In this paper, we proposed a MANET-based secure healthcare system to exchange medical data among portable nodes. Ensuring secure communication in the MANET-based healthcare system is one of the challenging issues. Healthcare system demands the sharing of confidential medical data among mobile nodes. So it is essential to provide secure information exchange in healthcare system by using strong cryptographic schemes. In this paper, we proposed a hybrid cryptographic algorithm for secure medical information exchange among mobile healthcare nodes. The proposed cryptographic scheme uses logistic map for key generation. Logistic map exhibits high security with less computational power. Our simulation results show that the proposed hybrid cryptographic scheme exhibits better security against various attacks in MANET-based healthcare systems. [ABSTRACT FROM AUTHOR]

This paper intends to apply the Intelligent Wireless Sensor Network (IWSN) to the archaeological excavation site and make the dynamic site of archaeological excavation can be monitored intelligently in real-time. This paper firstly discusses the structure and function of Wireless Sensor Network (WSN). Secondly, according to the problem of limited dynamic monitoring of WSN, an IWSN is established. The dynamic environmental monitoring of archaeological excavation sites is achieved by using Geographic Information System (GIS) and remote sensing technology combined with IWSN. Finally, this paper analyses the environmental monitoring results of the archaeological excavation site, the dynamic environmental monitoring location of the archaeological excavation site of the IWSN, and the simulation results of the Intelligent Wireless Sensor Network-Geographic Information System (IWSN-GIS) in the dynamic environmental monitoring of the archaeological excavation site. The results show that the Inverse Distance to a Power (IDP) algorithm in temperature and humidity monitoring data on the overall downward trend, the algorithm performance is relatively stable, and the algorithm performance is better than the other two algorithms. The monitoring performance of IWSN-GIS system is better than that of IWSN system. It shows that with the increase in the communication distance of sensor nodes, the relative error of different monitoring systems for the dynamic monitoring position of the archaeological excavation site is decreasing. IWSN-GIS can monitor the environment before, during, and after the archaeological site. This paper realizes the intelligent, scientific, and technological archaeology of archaeological excavation through IWSN, GIS, and remote sensing image technology, and provides technical support for digital archaeology in archaeological research. [ABSTRACT FROM AUTHOR]

This paper begins by outlining the evolution and current state of traditional wireless sensor networks, followed by an examination of the principle and architecture of wireless sensor networks, as well as the challenges that traditional wireless sensor networks face in environmental monitoring. This paper designs and develops a data visualization system for wireless sensor networks based on the visualization system and the advantages of other visualization systems, after analyzing and comparing the current visualization systems for monitoring wireless sensor networks. A real-time monitoring system for urban air quality based on wireless sensor network is designed to solve the problem that the traditional method of combining manual sampling with laboratory analysis for air quality monitoring is expensive and cannot carry out real-time online monitoring for multiple points at the same time. The system's implementation is based primarily on air quality monitoring data collected in the Shenyang area for visual display and analysis. The air quality monitoring system proposed in this paper has a complete structure and independent modules and is simple to use. The dynamic adaptability of the monitoring system is greatly improved by utilizing the self-adaptability and self-organization of wireless sensor networks, which brings great convenience to air quality monitoring. [ABSTRACT FROM AUTHOR]

Interferometric multispectral images contain rich information, so they are widely used in aviation, military, and environmental monitoring. However, the abundant information also leads to the disadvantages that longer time and more physical resources are needed in signal compression and reconstruction. In order to make up for the shortcomings of traditional compression and reconstruction algorithms, the stacked convolution denoising autoencoder (SCDA) reconstruction algorithm for interference multispectral images is proposed in this paper. And, the experimental code based on the TensorFlow system is built to reconstruct these images. The results show that, compared with D-AMP and ReconNet algorithms, the SCDA algorithm has the advantages of higher reconstruction accuracy and lower time complexity and space complexity. Therefore, the SCDA algorithm proposed in this paper can be applied to interference multispectral images. [ABSTRACT FROM AUTHOR]

Developments in information and related technologies have led to a wider use of the Internet of things (IoT). By integrating both virtual and physical worlds, IoT creates an integrated communication framework of interrelated things and operating systems. With the advent of IoT systems based on digital remote care, transferring medical data is becoming a daily routine. Healthcare is one of the most popular IoT applications and tries to monitor patients' vital signs during the day for weeks and to eliminate the need for hospitalization. In a healthcare system, many sensors are installed to collect the patient's information, including environmental monitoring sensors and vital and unstructured message sensors in order to reduce the patients' expenses. The IoT network contains flexible sensors in dynamically changing environments where sensors collect environmental information and send it to nursing stations for healthcare applications. Due to the wireless nature of IoT networks, secure data transmission in the healthcare context is very important. Data collected from sensors embedded in healthcare devices may be lost for various reasons along the transmission path. Therefore, establishing a secure communication path in IoT networks in the context of healthcare is of great importance. In this paper, in order to provide a reliable data transfer protocol in the context of healthcare, a reliable routing using multiobjective genetic algorithm (RRMOGA) method is presented. The contribution of this paper can be summarized in two steps: (i) using a multiobjective optimization approach to find near-optimal paths and (ii) using reliable agents in the network to find backup paths. The simulation outcomes reveal that the proposed approach, based on the use of the multiobjective optimization approach, tries to find optimal paths for information transfer that improve the main parameters of the network. Also, the use of secure agents leads to a secure information transfer in the network in the context of healthcare. Experimental results show that the proposed method has achieved reliability and data delivery rates, 99% and 99.9%, respectively. The proposed method has improved network lifetime, delivery rate, and delay by 14%, 2%, and 5.6%, respectively. [ABSTRACT FROM AUTHOR]

Large-scale wireless sensor networks (LSWSNs) are currently one of the most influential technologies and have been widely used in industry, medical, and environmental monitoring fields. The LSWSNs are composed of many tiny sensor nodes. These nodes are arbitrarily distributed in a certain area for data collection, and they have limited energy consumption, storage capabilities, and communication capabilities. Due to limited sensor resources, traditional network protocols cannot be directly applied to LSWSNs. Therefore, the issue of maximizing the LSWSNs' lifetime by working with duty cycle design algorithm has been extensively studied in this paper. Encouraged by annealing algorithm, this work provides a new elite adaptive simulated annealing (EASA) algorithm to prolong LSWSNs' lifetime. We then present a sensor duty cycle models, which can make sure the full coverage of the monitoring targets and prolong the network lifetime as much as possible. Simulation results indicate that the network lifetime of EASA algorithm is 21.95% longer than that of genetic algorithm (GA) and 28.33% longer than that of particle swarm algorithm (PSO). [ABSTRACT FROM AUTHOR]

Public art (PA) is a powerful tool for enhancing the environment in public spaces since it not only relieves the oppression caused by urban architecture but also enhances and beautifies urban public spaces. As DT (digital technology) develops so quickly nowadays, it offers PA significant technological assistance to achieve new functions, and changes in modern people's aesthetic preferences and psychological makeup also present new demands for PA. This essay explores the use of PA design in the creation of urban landscapes from the viewpoint of DT. In order to do this, this paper suggests a method for measuring the environmental impact of urban landscapes that combines landscape measurement and semantic assessment. Full-connection algorithm and greedy algorithm are introduced to identify urban functional types with high-dimensional characteristics for the boundary tree classification model of high-dimensional feature classification. The findings indicate that the public service area's producer and user accuracy are, respectively, 0.8783 and 0.7833. It offers a fresh concept for the identification of urban functional zones while solving the issues of low identification efficiency and poor accuracy. [ABSTRACT FROM AUTHOR]

Monitoring the ecological environment and creating protective landscapes have as their main objectives the rational and successful integration of available resources in accordance with regional needs while conserving their core nature. Landscape architects need to not only fully comprehend it but also develop it in practice if they are to ensure the maintenance of landscape design and plant configuration. In order to protect the environment, this essay discusses protective landscape design while emphasising environmental monitoring. The research shows that the strategy outlined in this paper has the lowest cost. Choosing a landscape that is inexpensive to upgrade has a big advantage over the costs connected to this method of developing a landscape. According to the ecological priority concept of ecological protection, rational planning and allocation of urban green space are of great urgency and practical significance for enhancing people's lives, fostering economic development, and creating a harmonious society in the current construction of a society focused on conservation. [ABSTRACT FROM AUTHOR]

Robots may be able to comprehend human emotions better by adding speech emotion recognition and environment monitoring functions to human-computer interaction systems. Robots can offer more humanized services by adapting to human emotions, resulting in a comfortable and cordial interaction between humans and robots. Improve the environment for communication and computer-human interaction and also interactive computer experience. In order for service robots to perform fluid human-computer interaction, this paper designs a sentiment analysis model based on CNN (convective neural network) to detect the feeling of interacting objects. It also builds a sentiment analysis model and an open domain dialogue system suitable for service robots. Examine the emotions experienced by the objects while they conversed. According to test results, the sentiment classification method used in this article performs more accurately on the dataset than the conventional model, and the final sentiment analysis model's F1 value can reach 0.931, which is better able to identify an emotional state. Using all voice samples as the input content of the network would eliminate the confusion between neutral emotions and other nonneutral emotions, boosting the accuracy of sentiment analysis in comparison to the fixed-length processing method of dividing or filling samples. [ABSTRACT FROM AUTHOR]

In order to realize the accurate prediction of spatial-temporal air quality index, this paper constructs a STAQI prediction model based on deep learning, including data processing, spatial feature acquisition, temporal feature acquisition, and STAQI prediction. Firstly, the spatial interpolation method is used to optimize the sample data set to provide reliable data; the improved graph convolutional network and the improved long short-term memory are used to effectively extract the spatial and temporal distribution characteristics of AQI data; and then, the extreme learning machine model is used to accurately predict and analyze AQI data. Simulation results show that the evaluation indexes RMSE and MAE of the constructed prediction model are 4.51 and 3.92, respectively, showing excellent curve fitting ability and AQI prediction ability. [ABSTRACT FROM AUTHOR]

The water environment is one of the basic elements that constitute the environment. It is an important place for the survival and development of human society, and it is also the most seriously disturbed and damaged area by humans. The pollution and destruction of water environment has become one of the major environmental problems in the world today. The essence of urban water space landscape design under the concept of integrating people's ecological design is the ecological landscape design of urban water spaces, while the development of ecological landscape design in the field of urban water space landscape design is still in its infancy, and the interpretation of its concept is also different. The ecological design of the landscape reflects a new dream of human beings, a new aesthetics and value: the true cooperative and fraternal relationship between man and nature. At present, the ecological design of urban water space landscape has not put forward a more accurate concept, clear principles and standards, and a complete and systematic theoretical basis, which requires further research, discussion, and continuous practice by this generation of designers to improve it. To this end, this paper proposed a research method on the integration of water environment governance in urban and rural spaces with natural ecological landscape design. This paper mainly talked about the status quo of water environment and its network sensor algorithm research and analyzed its coverage area one by one. Then, the water quality extraction is introduced in detail. And finally, the data analysis of the Beijing river waters, the analyzer rainfall, water quality, and so on are carried out in the experimental part. It could be seen from the experimental results that there were currently 22 reclaimed water plants in six urban areas of Beijing, with a daily water treatment capacity of 4.08 million cubic meters and a sewage treatment rate of 98%. As of 2016, 440 million cubic meters of reclaimed water has been reused. With the commissioning of the new reclaimed water system, the proportion of reclaimed water in the river and lake environment will continue to increase. [ABSTRACT FROM AUTHOR]

A wireless sensor network (WSN) monitoring system for saline-alkali-tolerant rice based on long-range + unmanned aerial vehicle (LoRa + UAV) has been proposed in this paper to meet the requirements of difficult deployment, low scalability, and poor network reliability of traditional farmland environmental monitoring systems. The system automatically forms a double-layer star topology network through the terminal node and central node (intranet), central node, and UAV mobile node (extranet). Data transmission is carried out through LoRa technology, routing planning is carried out for UAV mobile receiving nodes at different flight altitudes, and an early warning mechanism for UAV energy is added. It effectively prevents the UAV from destroying the communication capability of the external network due to energy exhaustion during operation. The system transmits information remotely to the server of the management center through a 5G network, which analyzes and processes the data and publishes it on the Web. The system has been tested in the field, and the reliable communication range of the node is 1∼4 km under the saline-alkali-tolerant rice environment, and the service life of the terminal node can reach more than 3 months. During continuous operation, the maximum packet loss rate of the internal and external integrated networks is 1.45%. The system can stably and real-time monitor saline-alkali-tolerant rice environmental information, and the error rate is less than 10%, which can meet the performance requirements of the saline-alkali-tolerant rice environmental monitoring systems, such as low power consumption, wide coverage, stability, and reliability, and has a good engineering significance. [ABSTRACT FROM AUTHOR]

In recent years, as people's demand for environmental quality has increased, it has become inevitable to monitor sensitive parameters such as temperature and oxygen content. Environmental monitoring wireless sensor networks (EMWSNs) have become a research hotspot because of their flexibility and high monitoring accuracy. This paper proposes a chaotic elite niche evolutionary algorithm (CENEA) for low-power clustering in EMWSNs. To verify the performance of CENEA, simulation experiments are carried out in this paper. Through simulation experiments, CENEA was compared with shuffled frog leaping algorithm (SFLA), differential evolution algorithm (DE), and genetic algorithm (GA) in the same conditional parameters. The results show that CENEA balances node energy and improved node energy usage efficiency. CENEA's network energy consumption is reduced by 8.3% compared to SFLA, 3.9% lower than DE, and 4.6% lower than GA. Moreover, CENEA improves the precision and minimizes the computation time. [ABSTRACT FROM AUTHOR]

In recent years, communication technology has improved exponentially, partly owing to the locations and nature of the deployment of sensor nodes. Wireless sensor networks (WSNs) comprise these sensor nodes and can provide real-time physical and environmental measurements. The sensor nodes have limited power, which reduces their lifespan, especially when placed in human-inaccessible locations. This paper reviews energy-efficient protocols for environmental monitoring applications and energy harvesting-wireless sensor networks. The dynamic deployment and communication challenges associated with environmental monitoring applications (EMAs) make this paper take into account the WSN protocol stack, focusing on the physical layer, network layer (routing), and medium access control (MAC). The paper will delve deeper into the security challenges of deploying sensor nodes for environmental monitoring applications (EMAs). The paper further describes scientific approaches that churn out innovative and engineering applications that must be followed to improve environmental monitoring applications. [ABSTRACT FROM AUTHOR]

Monitoring environmental water quality in an efficient, cheap, and sustainable way can better serve the country's strategic requirements for water resources and water ecological protection. This paper takes the Shaanxi section of the Weihe River Basin as a pilot project and aims to use the Internet of Things technology to develop water quality monitoring sensors, so as to realize the construction of low-cost, high-reliability water quality monitoring demonstration applications. First of all, we established the design of the water quality collection terminal, designed the low-power water quality sensor node, supported the Internet of Things protocol and the collection of various water quality parameters, and used networking for data transmission. Secondly, we use the ant colony algorithm-based system clustering model to obtain a cluster map of water quality monitoring tasks in a certain section of the Weihe River Basin. We take the task clustering graph as an example for analysis, optimize the monitoring model through the ant colony algorithm, and obtain the weight of the optimization index. The weight of the scheduled task limit of the monitoring point becomes larger, so the release of the monitoring task mainly affects the limit of the scheduled task of the monitoring point. Through the above work, we designed and implemented a set of online water quality monitoring system based on the Internet of Things and data mining technology. The system can provide reference for large-scale water resource protection and water environment governance. [ABSTRACT FROM AUTHOR]

Industrial production, military applications, and environmental monitoring all require corresponding positioning functions as science and technology advance. The location information service has gradually grown in popularity. However, large-scale applications will consume a lot of energy and cause environmental issues. Our further development will therefore focus on how to maintain low-carbon development and advance green technology. The improvement of triangular location algorithm is used in this paper to realize the research of low-power Bluetooth indoor location using the intelligent control project of green low-carbon buildings as the research object. The results show that the improved algorithm significantly improves the accuracy. The daily monitoring of the elderly and the alarm processing in an emergency are experimentally practiced and analyzed through the research of low-power Bluetooth indoor location algorithm. The research on intelligent control engineering of green low-carbon buildings is realized. [ABSTRACT FROM AUTHOR]

With the extensive use of the Internet of Things (IoT) in agriculture, the number of terminals are also grow rapidly. This will increase the network traffic and computing pressure of the centralized server. The centralized data processing mode used in traditional agriculture cannot meet the needs of the Internet of everything era. This paper designs a gateway based on edge-computing technology for monitoring crop growth environment. It uses virtualized container technology to package long-range wide-area network (LoRaWAN) server, pest identification, and environmental information data fusion functions into images. It forms integrated operation mode of multiple function in agriculture. The gateway applies message-oriented middleware to standardize and customize the data transmission among functional modules, clouds, and edges. Through simulation and field test, the designed gateway can achieve the functions of each module at the same time, the resource utilization, and the transmission quality are stable. The edge-computing gateway has the advantages of low cost, low latency, and low power consumption which has practical significance. [ABSTRACT FROM AUTHOR]

In sensor networks, UAVs are often introduced to assist data collection tasks. UAVs can operate as data ferry nodes, connecting distributed areas that are separated from each other. This paper proposes a data collection method for distributed wireless sensor networks based on UAV and introduces the idea of edge computing in it. In the single-hop transmission scenario, the K -means++ clustering method is used for sensor node clustering and cluster head election in the initial state. In the next rounds of data collection, UAV is used to assist in the election of new cluster heads and data collection tasks, taking into account the relative distance and the relative remaining energy relationship of the sensor nodes in their clusters. In addition, reasonable priorities are set for some nodes that have never been elected in the previous rounds and for the dead nodes. In the multihop transmission scenarios, for nodes that cannot deliver directly, the optimal relay node is selected for routing by comprehensively considering factors such as transmission angle, transmission distance, and remaining energy of the node in each cluster. The method proposed in this paper coordinates the overall energy consumption of sensor nodes in the environmental monitoring area, delays the death time of key sensor nodes, and extends the network lifetime. At the same time, an improved ACO is used to reasonably plan the data collection path of the UAV. Compared with the comparison scheme, the improved ACO can obtain a better shortest path length and has the fastest convergence speed when reaching the shortest path. [ABSTRACT FROM AUTHOR]

This paper uses the GIS technology to collect location and geographic information of the South Atlantic ecological environment and then uses the remote sensing image technology to extract and analyse the collected information to provide a strong basis for maintaining a healthy marine ecological environment. Based on multitemporal remote sensing images, this paper constructs an ecological vulnerability evaluation model for marine by coupling several ecological indicators, analyses the status of marine ecological environment and its dynamic changes, explores the driving factors of its changes, further analyses the relationship between ecological vulnerability, land use changes, and landscape patterns, and proposes targeted ecological protection countermeasures for marine ecological environment. This paper analyses and studies the quality control mechanism of marine environment monitoring data, the construction of marine environment evaluation model, and the automation of evaluation and early warning response based on the application of GIS, with the support of marine environment evaluation and early warning business, to enhance the availability and integrity of marine environment monitoring data, improve the execution efficiency of marine environment evaluation business and early warning response, reduce the risk of marine environment emergencies, and realize the integration and intelligence of marine environment evaluation and early warning, to improve the level of Informa ionization and management of marine environment evaluation business in marine management departments. The operational watershed ecological environment monitoring service system built in this paper, which integrates GIS, RS, GPS, data warehouse, and other information technologies, has the advantages of high accuracy of information extraction, convenient data management, good portability, and strong operability, which can provide a scientific basis for the unified scheduling management of the marine environment, ecological environment evaluation, and sustainable development planning of the economy, and it is of great theoretical and practical significance and can be used in other watersheds. Meanwhile, the unique environment of the ocean has endowed the marine microorganism with affluent diversity, which can display a variety of bioactivities. In this study, thirty-two seawater and sediment samples were collected from different depths within the scope of 5 m to 3203 m at 18 sampling sites in the South Atlantic Ocean. 1017 culturable strains were obtained after isolation and identification. The tip culture method was used to screen strains with antifungal and antiaflatoxigenic activities. The tip culture results showed that a total of thirty-one marine strains were confirmed to have significant antagonism against aflatoxin production with an inhibition ratio exceeding 80%, including 11 strains with a mycelial growth inhibition ratio exceeding 80% simultaneously. The variability of culturable bacterial distribution and diversity were studied by phylogenetic analysis of 16S rRNA sequences. Phylogenetic analysis of 16S rRNA sequences revealed a significant diversity of culturable strains. A total of 31 strains clustered into 13 genera: Marinobacter sp., Pseudomonas sp., Alteromonas sp., Idiomarina sp., Halomonas sp., Alcanivorax sp., Thalassospira sp., Jannaschia sp., Stakelama sp., Erythrobacter sp., Chengkuizengella sp., Bacillus sp., and Microbacterium sp. The 31 strains with antifungal and antiaflatoxigenic activities were dominated by populations of strains belonging to the genus Thalassospira (19.35%). To the best of our knowledge, this is also the first report to analyse the diversity of culturable bacteria with antifungal and antiaflatoxigenic activities in the South Atlantic Ocean from three perspectives: different media, different sampling stations, and different sampling depths. [ABSTRACT FROM AUTHOR]

Carbon neutral environmental protection is an important way to effectively control the rapid rise of global temperature, promote the green transformation of energy utilization, and promote green, low-carbon, and other technological progress. It is a new driving force for world economic development and growth. This paper explores the construction of wireless sensor model for carbon neutralization and environmental protection from the perspective of the transformation of energy Internet of things. This paper analyzes the development background and research status of energy Internet of things technology at home and abroad and determines the overall design scheme of environmental monitoring Internet of things system. Then, we design the overall scheme of wireless sensor model under the environment monitoring Internet of things system. An experimental test platform was built to test the performance of the environmental monitoring Internet of things system. The test results show that the wireless sensor can monitor and respond to physical impact, and the generated energy can realize wireless data transmission of about 20 m; the regional coverage and fixed-point Internet of things system can realize the real-time monitoring of environmental parameters such as light, temperature, humidity, and dust, interact with the data and instructions of the cloud platform normally, and work stably. The basic functions of the whole Internet of things system have been realized, including the alarm function of passive wireless impact sensing, the cloud real-time monitoring function of environmental data and the real-time sending function of cloud instructions, and the real-time monitoring of indoor and outdoor environment under two working modes. The task objectives set in the early stage of the whole system are realized. [ABSTRACT FROM AUTHOR]

Based on the wireless sensor network, this paper combines node monitoring data with intelligent network address management. Users can view real-time environmental data through a computer or mobile phone and can manually remotely manage the environmental adjustment equipment of the network address through the mobile phone. This article first discusses the research background of the subject, introduces the current domestic and foreign research status of WSN in environmental detection, and analyzes the reasons for choosing ZigBee network as the wireless transmission environment of the intelligent monitoring system. Secondly, the structure, layered model, and key technologies of wireless sensor networks are introduced, and it is pointed out that ZigBee technology, which has the characteristics of low power consumption, reliable communication, self-organization of the network, strong self-healing ability, and low cost, is very suitable for application in the environment. Then, it analyzes TI's protocol stack Z-Stack based on the ZigBee2006 standard and analyzes the network address assignment and addressing in Z-Stack, the process and steps of node binding, the routing mechanism and routing maintenance, and channel configuration. The realization of other functions was discussed in depth. During the simulation experiment, in the hardware design of the intelligent monitoring system, the network node was divided into two parts: the core board and the backplane. The crystal oscillator, power supply, antenna, and I/O port circuits of the core board were designed, and the data acquisition, relay, and power supply of the backplane were designed. Finally, this paper studies the data security issues in the environmental monitoring network and proposes two solutions to control network access and data encryption. Experimental results show that in terms of low-power design, the energy of the entire system is calculated to determine the factors that affect the power consumption of the system and methods such as increasing the node sleep time to ensure that the system can work for a long time. [ABSTRACT FROM AUTHOR]

In recent times, the deployment of wireless sensor networks becomes important in revolutionary areas such as smart cities, environmental monitoring, smart transportation, and smart industries. The battery power of sensor nodes is limited due to which their efficient utilization is much necessary as the battery is irreplaceable. Efficient energy utilization is addressed as one of the important issues by many researchers recently in WSN. Clustering is one of the fundamental approaches used for efficient energy utilization in WSNs. The clustering method should be effective for the selection of optimal clusters with efficient energy consumption. Extensive modification in the clustering approaches leads to an increase in the lifetime of sensor nodes which is a unique way for network lifetime enhancement. As the technologies were taken to next the level where multiparameters need to be considered in almost every application in clustering, multiple factors affect the clustering and these factors were conflicting in nature too. Due to the conflicting nature of these factors, it becomes difficult to coordinate among them for optimized clustering. In this paper, we have considered multiattributes and made coordination among these attributes for optimal cluster head selection. We have considered Multi-Attribute Decision-Making (MADM) methods for CH's selection from the available alternatives by making suitable coordination among these attributes, and comparative analysis has been taken in LEACH, LEACH-C, EECS, HEED, HEEC, and DEECET algorithms. The experimental results validate that using MADM approaches, the proposed APRO algorithm proves to be one of the better exhibits for choosing the available CHs. [ABSTRACT FROM AUTHOR]

In recent years, more and more researchers have paid attention to the three-dimensional target coverage of environmental monitoring wireless sensor networks (EMWSNs) under real environmental conditions. However, the target coverage method studied in the traditional two-dimensional plane is full of loopholes when applied in the real three-dimensional physical world. Most coverage algorithms usually only optimize for a single problem of target coverage or network energy consumption and cannot reduce network energy consumption while improving coverage. This paper proposes a novel binary adaptive clone shuffled leapfrog algorithm (BACSFLA) suitable for EMWSNs. BACSFLA has an excellent performance in the coverage of three-dimensional nodes, which can significantly reduce the network energy consumption of ENWSNs in the coverage process, and greatly improve the coverage of nodes. Through simulation experiments, BACSFLA was compared with simulated annealing (SA) and genetic algorithm (GA) in the same conditional parameters. The coverage rate of BACSFLA in EMWSNs is 3.9 % higher than that of GA and 5.4 % higher than that of SA. The network energy consumption of BACSFLA is 36.0 % lower than GA and 35.9 % lower than SA. Moreover, BACSFLA can significantly reduce the calculation time and get better results in a shorter time. [ABSTRACT FROM AUTHOR]

Sensor deployment is one of the major concerns in multisensor networks. This paper proposes a sensor deployment approach using improved virtual force algorithm based on area intensity for multisensor networks to realize the optimal deployment of multisensor and obtain better coverage effect. Due to the real-time sensor detection model, the algorithm uses the intensity of sensor area to select the optimal deployment distance. In order to verify the effectiveness of this algorithm to improve coverage quality, VFA and PSOA are selected for comparative analysis. The simulation results show that the algorithm can achieve global coverage optimization better and improve the performance of virtual force algorithm. It avoids the unstable coverage caused by the large amount of computation, slow convergence speed, and easily falling into local optimum, which provides a new idea for multisensor deployment. [ABSTRACT FROM AUTHOR]

Wireless sensor network (WSN) comprises of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, and pressure, and to cooperatively forward the collected information to the destination through the network infrastructure. As sensor nodes are energy constraint devices, therefore, the importance of energy efficient routing protocols has been increased. In order to minimize energy consumption, recently, a number of hierarchical routing protocols are proposed. For instance, LEACH is an elementary hierarchical routing protocol that employs clustering technique to achieve energy efficiency. A lot of research work has been performed to remove shortcomings and to improve the performance of hierarchical routing protocols. Therefore, a comprehensive review is required which can review state-of-the-art technologies, analyze functional and performance aspects, and highlight hierarchical routing protocol issues and challenges in WSNs. This paper proposes a taxonomy for the classification of existing hierarchical routing protocols for WSNs and analyzes the functionality and performance of existing hierarchical routing protocols. Moreover, it compares existing routing protocols to highlight key technological differences and provides performance comparison for the selected LEACH based routing protocols. Finally, the paper spotlights issues and challenges in existing routing protocols of WSNs, which can assist in future research for the selection of appropriate research domain and provide guidance in selection of energy efficient techniques in the design of energy efficient of routing protocols for WSNs. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) have become ubiquitous, permeating every aspect of human life. In environmental monitoring applications (EMAs), WSNs are essential and provide a holistic view of the deployed environment. Physical sensor devices and actuators are connected across a network in environmental monitoring applications to sense vital environmental factors. EMAs bring together the intelligence and autonomy of autonomous systems to make intelligent decisions and communicate them using communication technologies. This paper discusses the various architectures developed for WSNs in environmental monitoring applications and the support for specific design goals, including machine learning in WSNs and its potential in environmental monitoring applications. [ABSTRACT FROM AUTHOR]

Preventive protection of cultural relics is to make use of all the science and technology beneficial to the research and protection of archaeological heritage to predict the disease of cultural relics. The existing preventive cultural relics protection system has made some achievements in environmental monitoring, but the analysis and utilization of large data of cultural relics are still insufficient. In this paper, under the idea of multisource information fusion, a least squares support vector machine regression method based on multivariate time series wavelet correlation analysis is proposed to achieve accurate crack prediction of stone cultural relics. Firstly, the correlation of multivariate time series of stone cultural relics are quantitatively analyzed and the validity of characteristic variables of the crack is discriminated by wavelet correlation analysis; then, a least squares support vector machine prediction model is constructed based on the correlation obtained from the analysis; finally, the good performance of the method is verified by using the environmental monitoring data of the rock mass fracture in the North Qianfo Cliff of Dafo Temple in Binzhou City of Shaanxi Province. The experimental results show that the proposed method is more effective than the traditional backpropagation neural network, support vector machine, and relevance vector machine regression methods. This method is universal and easy to implement for multisource data prediction of nonmovable cultural relics diseases. It provides a scientific theoretical reference for the preventive protection of cultural relics. [ABSTRACT FROM AUTHOR]

Through a comprehensive theoretical basis and actual test analysis of the application system design and functional efficiency of the cloud platform, this paper puts forward an artificial intelligence environmental data monitoring and wetland environmental simulation method based on GIS remote sensing images. First, the basic storage and computing functions have been enhanced at the physical layer. Second, the middleware layer is more flexible in the use of management methods and strategies. There are many strategies and methods that can be used in combination. Finally, based on this, the application system design framework is more convenient and faster so that you can focus on business logic, and the strategic advantages of certain functions are very obvious. The method of object-oriented classification and visual interpretation using UAV image data and satellite remote sensing images from the typical recovery area and treatment area of wetland from 2016 to 2020 is given in detail together to extract wetland information and use GIS software for dynamic calculation. Using the wetland transmission matrix method, the distribution map of the characteristic types of the survey areas in the four periods and the conversion status of the characteristic types at each stage were obtained, and the effect of wetland treatment was quantitatively studied. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) is widely used in environmental monitoring, smart healthcare, and other fields. Due to its distributed nature, IoT is vulnerable to various internal attacks. One of these attacks is the packet-dropping attack, which is very harmful. The existing packet-dropping attack detection algorithms are unsuitable for emerging resource-constrained IoT networks. For example, ML-based algorithms always inject numerous packets to obtain the training dataset. However, it is heavyweight for energy-limited nodes to forward these extra packets. In this paper, we propose a lightweight evidence fusion-based detection algorithm (EFDA), which leverages the packet forwarding evidence to identify malicious nodes. Firstly, EFDA finds the sequence numbers of dropped packets and their corresponding source nodes. Then, it traces the routing path of each dropped packet and collects evidence for detection. The evidence stored by nodes around the path record the node's forwarding behaviors. Finally, the collected evidence is fused to evaluate the trust of nodes. Based on nodes' trust, the K-means clustering is used to distinguish between malicious nodes and benign nodes. We conduct simulation experiments to compare EFDA with ML-based algorithms. The experimental results demonstrate that EFDA can detect the packet-dropping attack without injecting packets and achieve a higher detection accuracy. [ABSTRACT FROM AUTHOR]

Emergency response to hazardous gases in the environment is an important research field in environmental monitoring. In recent years, with the rapid development of sensor technology and mobile device technology, more autonomous search algorithms for hazardous gas emission sources are proposed in uncertain environment, which can avoid emergency personnel from contacting hazardous gas in a short distance. Infotaxis is an autonomous search strategy without a concentration gradient, which uses scattered sensor data to track the location of the release source in turbulent environment. This paper optimizes the imbalance of exploitation and exploration in the reward function of Infotaxis algorithm and proposes a mobile strategy for the three-dimensional scene. In two-dimensional and three-dimensional scenes, the average steps of search tasks are used as the evaluation criteria to analyze the information trend algorithm combined with different reward functions and mobile strategies. The results show that the balance between the exploitation item and exploration item of the reward function proposed in this paper is better than that of the reward function in the Infotaxis algorithm, no matter in the two-dimensional scenes or in the three-dimensional scenes. [ABSTRACT FROM AUTHOR]

In view of the problems of poor air quality and serious soil pollution in the current ecological environment, an online monitoring of ecological environment pollution data in the Internet environment is proposed. The concentration of pollution sources that may appear in the atmospheric environment is analyzed through the analysis coefficient of ecological environment pollutants, and the specific grade data corresponding to the air quality index is determined. Observation and mapping are carried out for the area to be monitored, and then, the monitoring points are determined, the monitoring equipment is arranged, and the soil profile of the area is sampled in the monitoring area. The self-organizing neural network model is used to conduct spatial cluster analysis on the pollution of ecological environment pollution areas, evaluate the sensitivity of soil pollution, and build a land ecological pollution monitoring information model. Based on the Internet of Things technology and the comprehensive use of GPS, sensors, and other technologies and equipment, the framework of monitoring technology is constructed, and the online monitoring of ecological environment pollution data is completed. The experimental results show that the proposed method has high data accuracy in different locations and different seasons, which is consistent with the actual situation; because of the maturity of the Internet of Things technology, compared with the literature method, the method in this paper can provide a cost-effective data foundation, which is more cost-effective, and save time and energy. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) technology focuses on the application of information-sensing equipment, transmission network, and intelligent information processing technology. Through scientific management, it can achieve the rational use of agricultural resources, thus improving the ecological environment, reducing production costs, and improving the yield and quality of agricultural products. At present, the application of agricultural IoT technology faces problems including small network coverage, limited monitoring projects, high transmission cost, and short power supply time, which limit the popularity and ability of farmland environmental monitoring. In this paper, ns-3 is used to simulate the IoT for farmland environmental monitoring based on the long-range wide-area network (LoRaWAN) protocol. The simulation results show the transmission distance with good transmission quality under the LoRaWAN protocol. Furthermore, we analyze the comparison of the combination range of network transmission quality parameters under the two acknowledgment (ACK) mechanisms. Finally, we present the parameter combination range and suggestions to improve the network transmission quality, which provide a new basis for guiding the farmland environmental monitoring system. [ABSTRACT FROM AUTHOR]

With the continuous development of information science and technology, micro- and nano-fiber optic sensing technology has been widely used in the fields of medicine, communication engineering, and environmental monitoring, and fiber optic devices are widely available in the market because of their advantages such as anti-magnetic interference, corrosion resistance, light weight, high sensitivity, and transmission bandwidth. The purpose of this paper is to investigate the intrinsic correlation between micro- and nano-optical fiber devices and electronic information, introduce the fabrication process of micro- and nano-optical fiber, numerical simulations, and corresponding magnetic field experiments, explore the effects of polarization dispersion and polarization-related dissipation on the system, and enhance the sensing characteristics of micro- and nano-optical fiber through experimental design to maximize its functionality. The experimental results show that the refractive index and magnetic field exhibit a linear relationship with correlation coefficients of 0.995 and 0.994, respectively, when the external magnetic field is between 70 Oe and 300 Oe. [ABSTRACT FROM AUTHOR]

With the development of the society and economy, traditional water pollution monitoring methods can no longer meet the normal needs of work. Unmanned aerial vehicle remote sensing technology has gradually emerged, and it has shown a development trend of multimodel and multifunction. However, the application of UAV remote sensing technology in water pollution monitoring is in its infancy and has not formed a unified method and standard. This paper introduces the disadvantages of UAV Remote Sensing Technology in water pollution monitoring and provides a way to improve the application level of UAV Remote Sensing Technology in water pollution monitoring. In order to make full use of the advantages of remote sensing monitoring technology in water ecological environment monitoring, including wide coverage, fast analysis speed, accurate and reliable monitoring results, and large amount of information, according to the spectral effect of polluted water, a remote sensing inversion model of river and lake parameters is established to determine the water quality of rivers and lakes. Concentrations of pollutants in the body are inverted and analyzed. The analysis results show that the fitting effect of the inversion model is accurate and the accuracy errors reflected by the degree of dispersion and deviation are also acceptable. The inversion results of the concentration of river and lake characteristic parameters based on the Gaofen-1 remote sensing image data are in line with the actual situation. The research results can greatly strengthen the monitoring capacity of the sewage outlet and provide reference for related research on water pollution caused by the sewage outlet. [ABSTRACT FROM AUTHOR]

Grassland plays a key role in human production and life, especially in the protection and improvement of the natural environment, which cannot be replaced by other ecosystems, such as maintaining water and soil, preventing wind and sand fixation, maintaining carbon balance, affecting climate change, and producing biological products,.. More importantly, contemporary society attaches great importance to the development of agriculture and animal husbandry. Protecting and nurturing grassland plants and animals, maintaining biodiversity, rational grazing, and maintaining the sustainable development of the grassland ecological environment have become the top priorities. In view of the current serious grassland degradation and the decline of livestock carrying capacity, this paper proposes a grassland environmental monitoring system based on the ZigBee wireless sensor network. The system consists of a grassland wireless monitoring network and a remote PC, which realizes real-time and remote monitoring of environmental information, such as air temperature and humidity, light intensity, and rainfall that affect the growth of grassland pastures. Based on the requirements of the agricultural field data monitoring system, the overall framework of the system was designed and built. The system mainly includes two parts: the ZigBee wireless sensor network subsystem and the remote management software subsystem, and data communication is realized between the two through the Ethernet system data exchange protocol. Among them, the ZigBee wireless sensor network subsystem is deployed in the grassland area and mainly realizes the functions of real-time collection, processing, and wireless transmission of grassland data. The remote management software subsystem is mainly used for data reception, storage, and display and can maintain communication with the gateway node to support real-time monitoring of grassland data by remote browsers. [ABSTRACT FROM AUTHOR]

IoT (Internet of Things) usage in industrial and scientific domains is progressively increasing. Currently, IoTs are utilized in numerous applications in different domains, similar to communication technology, environmental monitoring, agriculture, medical services, and manufacturing purposes. But, the IoT systems are vulnerable against various intrusions and attacks in the perspective on the security view. It is essential to create an intrusion detection model to detect and secure the network from different attacks and anomalies that continually happen in the network. In this paper, the anomaly detection model for an IoT network using deep neural networks (DNN) with chicken swarm optimization (CSO) algorithm was proposed. Presently, the DNN has demonstrated its efficiency in different fields that are applicable to its usage. Deep learning is the type of algorithm based on machine learning which used many layers to gradually extricate more significant features of level from the raw inputs. The UNSW-NB15 dataset was utilized to evaluate the anomaly detection model. The proposed model obtained 94.85% accuracy and 96.53% detection rate which is better than other compared techniques like GA-NB, GSO, and PSO for validation. The DNN-CSO model has performed well in detecting most of the attacks, and it is appropriate for detecting anomalies in the IoT network. [ABSTRACT FROM AUTHOR]

Sensor networks can be used in many sorts of environments. The increase of pollution and carbon footprint are nowadays an important environmental problem. The use of sensors and sensor networks can help to make an early detection in order to mitigate their effect over the medium. The deployment of wireless sensor networks (WSNs) requires high-energy efficiency and secures mechanisms to ensure the data veracity. Moreover, when WSNs are deployed in harsh environments, it is very difficult to recharge or replace the sensor's batteries. For this reason, the increase of network lifetime is highly desired. WSNs also work in unattended environments, which is vulnerable to different sort of attacks. Therefore, both energy efficiency and security must be considered in the development of routing protocols for WSNs. In this paper, we present a novel Secure and Low-energy Zone-based Routing Protocol (SeLeZoR) where the nodes of the WSN are split into zones and each zone is separated into clusters. Each cluster is controlled by a cluster head. Firstly, the information is securely sent to the zone-head using a secret key; then, the zone-head sends the data to the base station using the secure and energy efficient mechanism. This paper demonstrates that SeLeZoR achieves better energy efficiency and security levels than existing routing protocols for WSNs. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) consist of a spatially distributed set of autonomous connected sensor nodes. The deployed sensor nodes are extensively used for sensing and monitoring for environmental surveillance, military operations, transportation monitoring, and healthcare monitoring. The sensor nodes in these networks have limited resources in terms of battery, storage, and processing. In some scenarios, the sensor nodes are deployed closer to the base station and responsible to forward their own and neighbor nodes' data towards the base station and depleted energy. This issue is called a hotspot in the network. Hotspot issues mainly appear in those locations where traffic load is more on the sensor nodes. The dynamic and unequal clustering techniques have been used and mitigate the hotspot issues. However, with few benefits, these solutions have suffered from coverage overhead, network connection issues, unbalanced energy utilization among the sink nodes, and network stability issues. In this paper, a comprehensive review of various equal clustering, unequal clustering, and hybrid clustering approaches with their clustering attributes is presented to mitigate hotspot issues in heterogeneous WSNs by using various parameters such as cluster head selection, number of clusters, zone formation, transmission, and routing parameters. This review provides a detailed platform for new researchers to explore the new and novel solutions to solve the hotspot issues in these networks. [ABSTRACT FROM AUTHOR]

The status information of complex status update applications (e.g., real-time environmental monitoring in disaster areas) can only be obtained after data processing. Therefore, the impact of data processing on age of information (AoI) cannot be ignored in complex status update applications. In this paper, complex status updates in emergency scenario are investigated, where some multiantenna unmanned aerial vehicles (UAVs) help resource-limited user devices (UDs) complete complex status updates which involve computing processes. To reduce average AoI, UDs' energy consumptions, and UAVs' energy consumptions in a balanced manner, the weighted sum of the three metrics is aimed to be minimized. Scheduling strategies (i.e., data transmission and computing start moments, service period, and flight radius) and power (i.e., data and pilot transmit power) allocation strategies are jointly optimized to reduce the weighted sum. The original problem is NP-hard. Thus, it is decoupled into some subproblems. Then, the near-optimal solution or stationary point of each subproblem is obtained by analyzing the characteristics of the subproblems. Finally, an iterative algorithm is proposed to alternately optimize the scheduling and power allocation strategies to obtain the suboptimal solution of the original problem. Simulation results show that the proposed algorithm can effectively reduce the average AoI and the energy consumptions of UDs and UAVs in a balanced way. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging is an area of active research with many applications in remote sensing, mineral exploration, and environmental monitoring. Deep learning and, in particular, convolution-based approaches are the current state-of-the-art classification models. However, in the presence of noisy hyperspectral datasets, these deep convolutional neural networks underperform. In this paper, we proposed a feature augmentation approach to increase noise resistance in imbalanced hyperspectral classification. Our method calculates context-based features, and it uses a deep convolutional neuronet (DCN). We tested our proposed approach on the Pavia datasets and compared three models, DCN, PCA + DCN, and our context-based DCN, using the original datasets and the datasets plus noise. Our experimental results show that DCN and PCA + DCN perform well on the original datasets but not on the noisy datasets. Our robust context-based DCN was able to outperform others in the presence of noise and was able to maintain a comparable classification accuracy on clean hyperspectral images. [ABSTRACT FROM AUTHOR]

As an important environmental monitoring equipment, the existing methane sensors or the traditional interferometer-based methane detectors have some drawbacks, such as low accuracy, large size, and complex calibration operations. Moreover, the optical path model and analysis method for the light interference methane sensor are not practical. In this paper, an effective light interference methane sensor is proposed based on a three-dimensional optical path model with point light source. Based on this model, the interference optical system is studied to illustrate the cause of the interference fringes. Furthermore, the influencing factors of the light intensity distribution are analyzed and an adjustment method for the interference fringes is proposed, which helps to simplify the assembling and calibrating operations. In order to improve the measurement accuracy, a temperature drift compensation method which includes a mapping table, a steady-state compensator, and a dynamic compensator is proposed. The mapping table is established between the output voltages of photoelectric detector, and the methane concentration, the steady-state compensator, and the dynamic compensator are proposed to eliminate the temperature drift. Finally, an experimental device for the light interference methane sensor is constructed to validate the interference fringe adjustment method and the temperature drift compensation method. [ABSTRACT FROM AUTHOR]

The Internet of Things is an emerging information industry. Applying the information collection, transmission, and processing technologies in the Internet of Things technology to environmental monitoring, environmental emergency, and other environmental protection supervision fields will greatly improve the speed and accuracy of environmental supervision and facilitate the scientific development of environmental protection. Through the Internet of Things, people can obtain a large amount of reliable real-time information, and it is not easy to be affected by time, place, and environment, while the wireless sensor network has the advantages of easy installation and low cost, so environmental monitoring through the Internet of Things is the future development trend. In this paper, in view of the current situation of water scarcity and serious water pollution in China, combined with the development trend and advantages of the Internet of Things (IoT), and based on the inadequacy of the existing microbial sensor data collection equipment, we propose a design scheme of microbial concentration monitoring system for waters based on IoT. The system is based on Zig Bee wireless sensor network to build a common data acquisition platform and design special hardware to carry out high-precision microbial sensor data acquisition in water and through the PC to complete the real-time measurement data storage, waveform display, and data processing. In this paper, the schematic diagram and PCB board design of the system hardware module NUC120 main control board, CC2530 RF board, Wi-Fi wireless communication module, and high-precision ADC acquisition module are completed and fabricated. Then, the four modules are combined to realize the development of the data aggregation node and data acquisition node of the dedicated Zig Bee wireless network hardware device. [ABSTRACT FROM AUTHOR]

Wireless sensor network (WSN) is usually organized in a particular area for achieving some specific tasks and functions. It has broad application prospects in military, environmental monitoring, disaster relief, and other many commercial areas. Measuring the significance of distributed nodes is the foundation of many applications of WSN. Therefore, this paper studies the distributed node measurement methods and approaches based on multiple attributes in wireless sensor networks to improve the accuracy of distributed node importance measurement. The entropy weight TOPSIS method is used to calculate the importance index of distributed nodes of degree centrality, eigenvector centrality, compactness centrality, betweenness centrality, K-kernel decomposition centrality, and aggregation coefficient; the PR value of each node is given by combining the PageRank algorithm; and then, the parameters α and β are introduced to calculate the comprehensive importance measurement results of each node, to finally obtain the importance measurement results of each node dynamically through the improved node deletion method. The experimental results of the research show that the proposed method can accurately measure the importance of distributed nodes in wireless sensor networks, and the accuracy is as high as 98%. [ABSTRACT FROM AUTHOR]

Mobile ad hoc network (MANET) is a miscellany of versatile nodes that communicate without any fixed physical framework. MANETs gained popularity due to various notable features like dynamic topology, rapid setup, multihop data transmission, and so on. These prominent features make MANETs suitable for many real-time applications like environmental monitoring, disaster management, and covert and combat operations. Moreover, MANETs can also be integrated with emerging technologies like cloud computing, IoT, and machine learning algorithms to achieve the vision of Industry 4.0. All MANET-based sensitive real-time applications require secure and reliable data transmission that must meet the required QoS. In MANET, achieving secure and energy-efficient data transmission is a challenging task. To accomplish such challenging objectives, it is necessary to design a secure routing protocol that enhances the MANET's QoS. In this paper, we proposed a trust-based multipath routing protocol called TBSMR to enhance the MANET's overall performance. The main strength of the proposed protocol is that it considers multiple factors like congestion control, packet loss reduction, malicious node detection, and secure data transmission to intensify the MANET's QoS. The performance of the proposed protocol is analyzed through the simulation in NS2. Our simulation results justify that the proposed routing protocol exhibits superior performance than the existing approaches. [ABSTRACT FROM AUTHOR]