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This study is conducted to measure the influences of corn farmers intention towards Internet of Things (IoT) for corn production in Perak. A set of questionnaire survey is distributed among corn farmers in Perak by applying Theory of Planned Behaviour (TPB) to collect data from the survey respondents. This study will be carried out based on three objectives, which is to determine corn farmers intention towards IoT for agricultural production in Perak. Secondly, to investigate the relationship of attitude, subjective norm and perceived behaviour control of corn farmers intention towards IoT for corn production in Perak. Finally, to identify the most influential factor of corn farmers intention towards IoT for corn production in Perak. 100 respondents were involved in this study. A purposive sampling method was applied in collecting data and analyzed using SPSS version 21.0. The expected findings from this study are high or positive intention of corn farmers towards IoT for corn production. There is significant value of relationship of attitude, subjective norms and perceived behaviour control of corn farmers intention towards IoT for corn production in Perak. Meanwhile the most influential factor of corn farmers intention towards IoT for corn production in Perak is attitude. The significance of this study is that hopefully farmers will be more aware and knowledgeable towards IoT to improve crop production performance since the technology offer multiple solutions in farm productivity. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is widely uses in agriculture sector for agricultural production. The objective of this research study is to determine the level intention of corn farmers to the new potential use towards IoT in agricultural production in Kelantan. The study focusing on to determine the factor that will affect the behavioral by using the most suitable theoretical framework which is Theory of Planned Beahavior (TPB) to predict the behavioral intention of corn farmers towards IoT in agriculture production. The intentions of farmers will be relying on three variables which is attitude, subjective norms and perceived behaviour control and it will determine the most influential factor of corn farmers intention towards IoT in agriculture production. The Theory of Planned Behaviour (TPB) consists of attitude which use to determine the attitude of farmers either they will use IoT in their farming or not, subjective norms are one of the social pressures from people surrounding the farmers performance in particular behavior and perceived behaviour control is farmers willingness and self-motivated in using IoT for their farming practices. The study will be conducted in Kelantan using online questionnaire survey and non-probability sampling methods to collect data from survey respondents. The sample size will be about 100 respondents where the question has been distributed to determine the level intention of corn farmers to the new potential use, the relationship between attitude, subjective norms, and perceived behavior control towards IoT in agriculture production and the most influential factor of corn farmer intention towards IoT in agriculture production. The data collected were than analyzed using descriptive analysis, reliability test, correlation analysis for Pearson correlation analysis and Spearman correlation analysis, factor analysis, and partial least squares structural equation modelling. [ABSTRACT FROM AUTHOR]

The delay in the doctor's arrival to the patient and the difficulty of diagnosis the patient's condition consistently is one of the health issues that this field suffers from it. Internet of things (IoT) based on health monitoring systems are very valuable for patients where the doctor can know the patient's condition from anywhere in the world. This research presents a real-time Smart Healthcare Monitoring System Based on an IoT Environment. This system will be able to measure values of body temperature, heart pulse rate, and oxygen saturation in patients using a small device that contains a set of sensors such as a body temperature sensor, heart rate sensor, and oxygen sensor, as well as a processor that collects data and transmits it via internet, so a specialist can view the results any time and from any location by utilizing a mobile application. this paper aims to present an architecture design in order to develop of health monitoring system and to describe the main required components proficient for producing efficient and accurate health monitoring. In this work, the high price and size of the device were taken into account, and the problem was addressed by reducing the size of the components and connecting them with a small "Arduino mini", which in turn is low in cost. This system is efficient because of its low power consumption, ease of setup, great performance, and quick response time. [ABSTRACT FROM AUTHOR]

PDAM Tirta Silau Piasa Asahan To detect and control leaks in the water distribution pipe, a prototype system was designed using 2 flow meter sensors, 2 moisture sensors, and two solenoid valves. Based on the test, the system works if the moisture sensors and flow meter detect a leak. The leak causes the water discharge to be less than 30 L/second. Leak messages are sent to cellphones and LCD screens within 5 to 8 seconds after detection. [ABSTRACT FROM AUTHOR]

Currently, there are still very many Kindergartens whose security in checking the identity of the introduction or pick-up is still manual, some even do not do identity checks. This is felt to be less able to overcome parental concerns about child crime which is increasingly happening. We need a computer-based tool to increase child safety when in delivery and pick-up by knowing who the delivery person and pick-up are. If the child is delivered or picked up, then the delivery person or pick-up only needs to scan the Student Card by waiting for the successful display on the LCD and also the web display so that the delivery or pick-up data is stored in the database, then the child will be called automatically at the time of pick-up and the parents receive an SMS notification when the child is picked up. Based on the results of the overall design of a student security system using RFID that has been carried out, the results of the design that has been tested overall have been running and active as expected by the author with a success percentage of 94%. [ABSTRACT FROM AUTHOR]

A Hydropower Plant is one of the generators that is driven by using kinetic energy, by utilizing the flow of flowing water, by converting the flow of water into kinetic energy so that it can rotate the turbine, the kinetic energy of the turbine is converted into energy of generator motion. Hydropower have dams/reservoirs as temporary water storage from upstream of the river, by using dams the stored water can be helpful for hydropower generation. But because the weather characteristics in Indonesia can cause river flow instability which can cause river discharge to change suddenly if conditions are dry season or rainy season to overcome problems when the river overflows with the application of the internet of things, applying real-time water level monitoring technology. The application of the internet of things to hydropower dams can help residents and State Electricity Company employees to monitor the water level. Monitoring tools can display water levels in real time through mobile applications, charts, and databases. The data shown in the database can be downloaded as a data sheet. The graph is displayed using the Thing speak web server according to the sensor data installed on the dam with the results of the Wemos R3 microcontroller test getting an average peak load data at a height of 370 cm which causes low tide in the Way Besai hydroelectric dam. [ABSTRACT FROM AUTHOR]

The transition from using fossil energy to New and Renewable Energy (EBT) is something that is absolutely necessary. One of them is the use of solar panels as an alternative energy source, energy sources from solar panels can be utilized in the chicken farming sector to assist in the process of hatching eggs using an egg incubator. The energy source for egg incubators usually uses electrical energy from the National Electric Company, but if a short circuit occurs or a power outage occurs, the device will not function, while the egg incubator must maintain temperature and humidity stability in hatching eggs. Monitoring the energy produced by solar panels and monitoring the room temperature of the egg incubator so that it can work optimally, the Internet of Things (IoT) uses the Blynk android application. Testing the voltage, current and power readings using PZEM-017, the largest error difference on the voltage reading is 0.15%, and the smallest difference is 0.00%. The biggest error difference in the current reading is 1.62% and the smallest difference is worth the average error of 0.64%. Testing the temperature and humidity readings of the egg incubator using DHT-11, the largest error difference in temperature readings is 2.31%, and the smallest difference is 1.58%. The largest error difference in humidity readings is worth 20.37% and the smallest difference is worth the average error value of 11.11%. Solar Power Plants (PLTS) can help turn on egg incubators, but PLTS cannot overload egg incubators for 24 hours so they still need energy from PLN. The highest voltage generated by the solar panel during the 5 days of research is 13.79V, the highest current is 5.51A, and the highest power is 73.6W and the highest battery voltage is 13.6V. [ABSTRACT FROM AUTHOR]

Narrowband IoT (NB-IoT) are currently developing so rapidly. This can encourage the creation of many innovative and implementable products that are very useful in everyday life. One of these products is the use of NB-IOT for monitoring cage conditions, maintenance and increasing livestock productivity amid difficult conditions to control and know the state of the cage manually. In this study, an automated system will be designed that can keep the cage ideal including the temperature of the cage, humidity, levels of ammonia (NH3 and CO2) as well as feeding/drinking foals automatically and periodically. This research was compiled using a combination of several sensors that are assembled on a microcontroller such as temperature sensors, humidity sensors, ammonia sensors, water level sensors and pH sensors. The program is connected to a panel and through the internet network control and monitoring can be carried out via mobile devices and desktop devices. From the overall test, it was found that the results of easy control of the chicken coop for owners and workers, maintained poultry health and maximum yield of livestock products. [ABSTRACT FROM AUTHOR]

Timely identification of diseases in crops and taking immediate actions to prevent them from being completely destroyed is a key part of agricultural production. Environmental challenges like unfavorable weather conditions and climate changes directly affect the plant growth and it causes viral infections that can lead to the eradication of the crops. Microorganisms such as bacteria and fungi can also cause various diseases in plants. In order to provide the accurate and better solution for a plant problem, the farmers first need to identify the exact kind of illness that the plant is having. The existing method of manual diagnosis of plant diseases by a field expert is time consuming as well as costly. Farmers cannot afford the cost of frequent visits to remote laboratories for diagnosis. The use of advanced and effective deep learning models can solve this problem and predict plant diseases at an early stage. IoT has become very popular in the agricultural industry as it provides state of the art solutions to plant problems. This paper aims to study the recent related works on this area and to analyze the advanced methods and models used in the implementation and to allow future research to learn larger capabilities of IoT and Deep Learning in proactively detecting the plant diseases with improved system performance and accuracy. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a rapidly evolving technology. Interrelated devices and sensors transmitted data via the network to resolve issues and provide additional services. Hospital treatment, remote control of equipment, and M2M contact, among other services, are provided to users without the involvement of humans. It increases the availability of Internet-connected devices in our daily lives, bringing with several benefits as well as security risks. There are a various of ML approaches that can be utilized to protect IoT from various types of threats. Machine Learning (ML) methods are used to generate precise outputs from huge complex data, which can then be utilized to predict and identify risks in IoT network. This chapter, carried out a comparative review of previous researches and studies on attack identification using Machine language techniques. The objective of this work is to give a systematic study of ML techniques that can be utilized to create upgraded attack detection models for IoT frameworks [ABSTRACT FROM AUTHOR]

The quality of the water needs to be continuously evaluated to maintain a safe supply of drinking water. For this goal, a novel strategy based on water quality monitoring system using IoT has been put forth. In this paper, we propose the design of a real-time water quality monitoring system based on the Internet of Things. In this developed system consists of sensors that track many aspects of water quality, including pH, turbidity, dissolved oxygen, and temperature. The microcontroller processes the sensor-measured quantities and sends the transformed values to the cloud. Finally, using cloud computing, sensors data can be viewed on an internet browser application. These sensors are installed on an autonomous watercraft. The boat is equipped with an ultrasonic sensor that detects any movement. [ABSTRACT FROM AUTHOR]

In today's technological era, every home, industry, and commercial place has numerous electrical appliances to perform all tasks quickly and with ease. It also mandates every home to have a three-phase electrical supply and leads to a growing increase in energy demand. The traditional and new equipment have been modernized by making them very smart and energy efficient to manage the continuously growing energy demand. In the previous decades, power saving was done during the monitoring of the load alone, which was not very effective. The main objective of this paper is to continuously monitor the power consumption of the load and also to save energy in an efficient way using the Internet of Things (IOT). In a three-phase supply, whenever there is a phase shift, phase angle changes and so it has to be corrected. This system helps to correct the phaseangle automatically during the reverse condition. The IoT devices will be used to share voltage and current values on the website. Power management is also carried out to ensure proper power consumption. The monitoring relay is the main component of the system, and it checks the phase sequence, overvoltage, and undervoltage. A multifunction monitoring relay based on a microcontroller integrates the voltage and current values to calculate the supply's phase angle. The Proteus software was used for the website updates. [ABSTRACT FROM AUTHOR]

With the growing number of security breaches, the necessity for better security procedures and protocols has grown as well. According to a reports, lakhs of robberies are occurring in the United States of America each year. Though India is a developing country, these types of robberies are considerably more common. The primary purpose of this work is to develop a security solution that can help combat this. This paper primarily aims to design a software that is built from the ground up for detection of face, leading to facial recognition and finally, providing information to the user or the owner of the software if any unfamiliar face is there which is not a part of the database. The aim is to notify the owner about any unfamiliar person that is present and unrecognized by the camera. In case if the face is not recognized, alerts will be sent via SMS and Email. Some software has limited forward compatibility and can be difficult to run on weak hardware, thus it is necessary to have a software which is more powerful and easily run on the weak hardware. The proposed work has a great scope in the future applications ranging from simple automatic locking systems in households to an attendance system in corporate offices and even for an antiterrorism system. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) plays a significant role in the research and development of an intelligent environment and provides many opportunities for people. Nowadays IoT is everywhere for making electronic devices more competent and more comfortable. Because all devices and modules in an IoT is linked via internet connection. Therefore, anyone can hack the device and operate according to the hacker's desire. To retain the reliable connectivity and accessibility of IoT, it is essential to set up secure links for end-to-end communication with proper authentication. The proxy-based wireless sensor networks connect tiny sensor nodes and actuators. The WBAN is connects all the sensors and actuators that is implanted on cloths or inside our body. The primary application of IoT is wireless body area networks which help people of all ages to assist medically during a medical emergency. Also, the medical data contains some sensitive files and reports; hence maintaining the security and privacy issues in WBAN is essential. Because hacking important files and records of a patient, is a life threat. This proposed work discusses a token mechanism-based lightweight multilayer verification protocol for sensing the WBANs and is energy efficient. This protocol is based on token system for the enhancement of security. There are many sensor nodes in WBAN. Between each sensor node, we implemented a cluster verification protocol and cluster key formation algorithm. The novel algorithm involves low energy consumption and minimizes the computational cost coherently. [ABSTRACT FROM AUTHOR]

Talempong is a traditional musical instrument from the Minangkabau tribe in West Sumatra, Indonesia. The challenges of learning Talempong musical instruments are the lack of availability of Talempong musical instruments, limited trainers or music teachers to train and evaluate, and limited time for students to learn. The Internet of Things (IoT) has the ability to automate activities, integrate with various sensors, and store data on the internet that can be accessed anytime and anywhere. In this study, we developed an IoT-based Talempong musical instrument learning system. The system was built with an IoT development model consisting of five phases. Hardware components consist of LED lights, vibration sensors, microcontrollers, and wiring, whereas the software component is a website-based application that displays the results of student learning activities and programs for the Talempong training level. The communication protocol used in the system is the MQTT protocol. The system implementation results show that the IoT-based Talempong system follows the functionality and performance designed to solve the problem of learning the Talempong musical instrument. The performance results show that hardware and software components have worked, the delay from the vibration sensor to the microcontroller is always under 1 second, and the system provides 100% feedback on Talempong learning activities at level three. This prototype can be a reference for developing an application based on IoT for music education. [ABSTRACT FROM AUTHOR]

Internet of things is a little world of connected things with the integration of smart devices like sensors, actuators, gateways, gadgets etc. Smart cities, Smart home, Agriculture, Disaster management, Smart Grid, Healthcare system are some of the major applications of the Internet of Things. Machine Learning is another paradigm of the technology revolution and used as a predictive analytics technique. It is employed in about all the areas for the analysis of data. In this paper we proposed a system for the diagnosis and prediction of diseases by unification of Internet of Things and Machine Learning. Data generated by medical sensors, gadgets is fed to semantic engine to make it semantic interoperable and Machine Learning is further employed for predictive analytics. Semantic engine used Resource Description Framework (RDF) to convert data into a common format and data is retrieved using SPARQL queries and GraphDB. [ABSTRACT FROM AUTHOR]

This paper proposes a security and privacy detection (SPD) project for shielding the IOT transmission network structure with an aspect of lowering the latency concerns that come from the cryptographic estimation cost. The recommended SPD project is structured relative to the homomorphic cryptographic structure that allows the edge interchange to classify the similar query texts for verifying and decrypting them in a single level. Security discussion represents the capacity of the recommended SPD project in shielding the IoT transmission structure from different of security attacks. The evaluation analysis has been done on the proposed SPD scheme to show the efficiency of the SPD project in lowering the latency concerns being developed by high cryptographic estimation cost. [ABSTRACT FROM AUTHOR]

Now a day's Internet of Thing's (IoT's) is considered growing technology. Ever increasing demand of IoT devices must have reliable channels for communication therefore, security needs to be ensured. Wireless enabled IoT use to have many real-time applications which include smart education, intelligent transportation, smart home, smart grid, health care and farming etc. Data collection can be made possible with the help of massive IoT devices. Intruder directly sends illegal data packets which lead to hijack overall network. IoT-networks have improved human experience in many real-time applications. Cyber-security threats usually limit computational resources. Therefore, detection of cyber-threats is the main problem for IoT-networks. This paper presents a novel concept of leNet model-based IDS to detect cyber- attacks. Although, two benchmark datasets such as IoTID20 and CICIDS2017 are utilized for simulation. LeNet model is compared with other traditional techniques like linear discriminant analysis, quadratic discriminant analysis, support vector machine and multi-layer perceptron. Accordingly, metrics like accuracy, precision, recall, F1-score, confusion matrix and correlation matrix are used for performance evaluation. Extensive analysis is performed which indicates that with IoTIDS20 dataset, LeNet achieves recall-99.91%, precision-99.74%, F1-score-99.83% and accuracy-99.68%. While, using CICIDS2017 dataset, LeNet presents optimal results in terms of recall-97.96%, precision-96.41%, F1-score- 97.18% and accuracy-98.87%. Proposed LeNet model is light weighted and adaptable. [ABSTRACT FROM AUTHOR]

Nowadays, the IoT (Internet of Things) plays a crucial role in many requirements of daily life, where healthcare, safety, security, and energy management are considered some of the most significant applications that rely on IoT in their operation. One of these requirements is to perform a smart home that can be controlled by a smartphone, to operate and switch off the electrical or electronic devices and sensors. This can be executed depending on the IoT capabilities to simulate and operate a smart home. This paper focused on practical home automation that involves several devices like a webcam, humidifier, ceiling fan, air conditioner, etc. By using some sensors and devices, the designed smart home is controlled and monitored. The findings revealed that smart devices and sensors can be easily added to the home gateway; additionally, this system will make real-life easier and more comfortable. [ABSTRACT FROM AUTHOR]

As the world is evolving and technically advancing, people need a lot of gadgets to be interconnected for the smooth functioning of the system and every gadget requires a certain amount of energy. Now with so many gadgets being used energy consumption has become a major threat to the world. Some devices take a lot of time to charge, and sometimes users even forget to turn off the charging port which leads to more energy loss and thus more carbon emissions. The proposed solution is to build a device that not only charges the devices but also stores the energy. The port auto-cuts the charging when a device is fully charged and stores the extra energy. In this paper, we have gone through different papers and have analyzed the algorithm they are using and their disadvantages. This survey contains a wide range of algorithms used for energy saving by researchers so as to learn more about green IoT and energy saving. Researchers can use this survey's insightful results as a guide to developing novel systems for energy storage. [ABSTRACT FROM AUTHOR]

The increase in world population witnesses the birth of strange diseases/viruses such as covid 19 that challenge the present healthcare system, but it also leads to the development of new technologies that help us fight those diseases/ viruses. The Internet of Medical Things (IoMT) is playing a crucial aspect in providing quality health treatment and reducing cost and error for both patients as well as frontline health workers. The goal of IoMT is to develop the advancement of intelligent and effective IoT devices in the health industry that can save countless lives by using advanced sensors and communications devices that help in the early prediction of critical diseases. This paper presents a succinct review of emerging technologies in healthcare, the role of IoMT devices, their applications, and the challenges that arise while implementing them. A discussion has been made on various security threats that come with the development of such devices, and their aftereffects on individuals and on health workers. [ABSTRACT FROM AUTHOR]

The Internet of Things and applications of Internet of thing (IoT) are becoming popular among various users nowadays, because it makes their life more easy. Because of its spread, attacks that target these various devices have increased dramatically, that may cause the unavailable of entire system. Some types of these attacks are man in the middle attack, sybil attack, denial of service attack, and replay attack. So, whenever the attacks have increased, solutions of the detection of malware in the internet of thing have also increased. one of the current solutions is a deep learning algorithms, In many research fields, deep learning techniques have demonstrated their capacity to detect anomalies accurately. [ABSTRACT FROM AUTHOR]

The wireless sensor network (or WSN) is the most recent technology that is going to be the upcoming era of the internet that link various physical objects who connect with each other without required to the human interactions. Even so, security play's considerable role in network in order to prevent the not data misuses, modification of data, authorized access, etc. The WSN communication could be secured by used a light-weight cryptography, that is the lighter kind of cryptography. About 50's lightweight cryptography algorithms (basic encryption algorithms) were presented in the recent years with a focus on a certain application, in addition to many other methods have been made by the study for the NIST recent times. To be able to present an alternative view of the WSN security problems and the utilization of lightweight encryption to protect it, this study, a review was presented to review several existing light weight algorithms which could serve this area, along with make comparison among these algorithms relating to performances, implementation, and models of attacks and the protest to these attacks. [ABSTRACT FROM AUTHOR]

Recently, solar power represents one of the most stable and important renewable energy resources in our life, its importance increases every second because the planet will be run out of fossil fuel in the near future, but sometime uncertain fluctuations appear duo to rain, dust, clouds, and heat which prompts the issue of power supply interference. So that, in the traditional way, the solar panels have to be check from time to another to figure out if they still work correctly, and that could make either the maintenance cost will be high, or there will be loss in the performance, that could be obvious in a solar system of large number of panels. As a result a better way to check the solar cells is needed to make the performance better, especially in case of a large number of solar panels. In this paper, a study will be made about solar system consists of an array of solar panels and photovoltaic parameter in each of them. The main purpose is building a system which works on fault detection. This study depends on Smart Monitoring Device (SMD) sensors, which connected to each PV panel. These sensors collect the measurements periodically, and send them to an IoT central server, in order to detect the faults to correct them as soon as possible and improve the efficiency of solar panels. The results showed that the AC voltage from the applying the system of Solar Voltage 1when the fault occurs as the maximum is 30.62 V and average is 17.9 V while the Solar Voltage 2 as max is 31.05 V, and average is 18.15 V. The AC power consumed per unit time (0.1 seconds is 20.573 W to 0.8 seconds is 20.592 W. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is one of the modern technologies currently used. The IoT system consists of interconnected devices such as technological devices, sensors, and actuators that can collect data to transfer it without human intervention. Internet data could be reached either through a private web page via a smartphone or a personal computer. IoT has increased uses at the present time, which is used in industrial, health, agricultural sectors, etc. To do that, the cities will be Smart to enhance the daily activities of users by reducing the time consumed to access the required information. This paper provides a prototype for the application of a Smart campus that depends on the IoT. This paper also includes choosing the building of science departments in the College of Engineering Technology Najaf as an example of a Smart campus. The Packet Tracer v8.2 from Cisco involved many devices and components used to simulate the network in reality. [ABSTRACT FROM AUTHOR]

The 2.45 GHz area is used to demonstrate the operation of a penetrating windmill-like surface with wireless energy harvesting that is comparable to the polarization-independent collecting of electromagnetic waves (Wifi). An improved wireless energy harvester's efficiency can be achieved by reducing the susceptibility of the reception to polarization and wave angle. Four identical metal wires that have been 45 degrees rotated make form the meta-surface unit cell. A wide-angle, polarization-insensitive behavior, exceptionally high absorption coefficients, and extreme compactness characterize the simulated unit cell. An 86% harvesting efficiency at 2.45 GHz is achieved by building and simulating a three-dimensional metamaterial harvester. For applications requiring great efficiency, the suggested meta-material design may be particularly intriguing. [ABSTRACT FROM AUTHOR]

Managing IoT networks is complicated due to the increasing number of devices in the network. Furthermore, several challenges are raised regarding communication, traffic patterns, and characteristics. The network scalability should be evaluated by modelling the behaviour of IoT devices, particularly traffic patterns. However, as IoT is relatively new, it is challenging to model thoroughly. Many models are proposed, but no standard modelling paradigm is available for real-world complex IoT-based scenarios addressing all the requirements. This research provides an overview of network analysis and modelling, focusing on the central issues to introduce specific knowledge that helps to understand the traffic and guide the new research directions in network traffic modelling and analysis. [ABSTRACT FROM AUTHOR]

The Internet of Thing (IoT) is an innovative technology designed to integrate tangible artefacts with the digital era, resulting in the development of new digital services to improve and ease our lives. Despite the advantages of IoT technology in a variety of industries. The existing centralised IoT architecture has a number of issues, including single point of failure, stability, safety, accountability, and data integrity. Such issues are impeding the growth of IoT in the future. To address the a forementioned issues, distributed ledger technologies are regarded as promising and feasible solutions. The blockchain is one of the most prevalent and widely used forms of distributed ledger technology. The combination of IoT and blockchain technology has numerous advantages. The combination of IoT and blockchain technologies will provide numerous benefits. This article demonstrates the fundamentals of IoT and blockchain technology in order to provide a thorough analysis of the architecture of the combination of IoT and blockchain technology. In addition, this study provided a comprehensive description of the combination of the blockchain with the IoT platform from a variety of perspectives in order to address IoT's shortcoming. The service function of blockchain in IoT applications is demonstrated. Finally, the prospective applications of blockchain technology to IoT fields are discussed. [ABSTRACT FROM AUTHOR]