IoT Technology Research Articles

A Platform for GHG Emissions Management in Mixed Farms

This research introduces an innovative platform designed to manage greenhouse gas (GHG) emissions in mixed farms. Emphasizing the urgent need to address GHG emissions, particularly methane (CH4) and nitrous oxide (N2O), the platform targets mixed farming systems where the interplay of livestock and crop production significantly contributes to environmental impacts. Our methodology is grounded in comprehensive data collection, encompassing soil data, energy consumption, and detailed livestock information. Utilizing the Agricultural Internet of Things (AIoT), it facilitates real-time data acquisition and analysis, providing insights into various farm activities’ GHG emissions. This approach allows for precise monitoring and management of emissions from different sources, including enteric fermentation in livestock and fertilizer use in crop production. Results from the application show its effectiveness in offering a clear and interactive visualization of GHG emissions, aiding farmers in making informed decisions for sustainable farm management. The platform’s user management system, coupled with advanced data processing and visualization capabilities, underscores its potential as a vital tool for sustainable farming. Conclusively, Solution4Farming represents a significant advancement in digital agriculture, combining IoT technology with sustainable practices. Though initially designed for Romanian cattle farming, Solution4Farming’s anticipated expansion to various farming environments suggests a broader impact and relevance in sustainable agriculture.

The Hybrid Cryptographic Algorithms for Secure RFID Data Protection in The Internet of Things

RFID is often used by companies to identify employees and company assets, as well as in supermarkets to identify goods when shopping. In this increasingly sophisticated era, IoT technology has wide applications. The use of RFID technology in IoT networks may pose vulnerabilities to security and privacy because it contains sensitive information, and RFID data transmitted over communication channels is vulnerable to attacks. IoT technology has characteristics such as high autonomous data capture rate, network connectivity, and interoperability for services and applications. Therefore, this research aims to improve the security of RFID data by taking into account the characteristics of IoT. The method used is hybrid cryptography by combining AES (Advanced Encryption Standard) and ECDH (Elliptic-curve Diffie-Hellman) keys. AES, as a commonly used symmetric cryptography, is chosen to protect the data, while ECDH, as the latest asymmetric cryptography, is used for a faster and more efficient process compared to previous asymmetric methods. This study utilizes the Python programming language on Jupyter Notebook. The initial step of the study involved scanning the RFID data to be secured and configuring the key on ECDH. The subsequent process included encryption and decryption of the data. The study successfully tested the success of encryption and decryption on RFID UIDs. The test data includes the result display of the hybrid encryption, the encryption and decryption processing time, and the file size of the encryption (ciphertext) and decryption (decodetext). These results show an excellent level of security for RFID UIDs. Only those with a specific key can know the contents of the cipher. It should be noted that this study was only conducted at the program level and was not implemented on hardware. Therefore, the results can be a valuable reference for future research.

IOT BASED SOLAR POWERED PUMP FOR AGRICULTURAL IRRIGATION AND CONTROL SYSTEM

This paper focuses on the implementation of a solar-powered pump system integrated with IoT technology for agricultural irrigation control. By leveraging the properties of the system, such as humidity, temperature, soil moisture, time collection based on solar panel activity, and peculiarities like using a mobile app and automated control, the project aims to provide an efficient and sustainable solution for irrigation.The system utilizes humidity sensors strategically placed in the soil to monitor moisture levels, enabling precise irrigation control. To enhance user experience and accessibility, a user-friendly mobile app is developed. This app allows farmers to remotely monitor and control the irrigation process, providing real-time data, irrigation scheduling options, and the ability to adjust system settings. Through IoT integration, the system enables automated control of the pump based on predefined parameters. By analyzing sensor data, including humidity levels and solar panel activity, the system autonomously adjusts irrigation operations, reducing manual intervention and improving overall efficiency. From the acquired results, at a temperature of 37.2 0C, the humidity level is low at 49.6%, thereby activating the irrigation pump which resulted to decrease in temperature at 26.70C after a period of 1hr 48mins with the humidity, and soil moisture levels at 73.9%, and 88% respectively. The developed system monitors and balance the soil moisture level through automated irrigation process which is solar powered and remotely managed.

SUBSTANTIATION OF REQUIREMENTS FOR THE STRUCTURAL AND ALGORITHMIC ORGANIZATION OF AN IOT MONITORING SYSTEM FOR SOIL AND CLIMATE PARAMETERS IN AGRICULTURAL CROP ENTERPRISES

Relevance. As one of the key sectors of the global economy, agriculture plays a decisive role in shaping sustainable economic development and ensuring food security worldwide. Achieving satisfactory indicators of food security and the export potential of agricultural products is a domestic priority for economic recovery and sustainable development. Accordingly, the development and implementation of modern digital technologies in agriculture becomes a strategically important task. The utilization of cutting-edge technologies for the agricultural sector, coupled with the improvement of cultivation and processing methods for agricultural crops, is a key element in ensuring the resilience and efficiency of the industry. The main aim is to conduct a critical analysis of existing solutions in the field of information monitoring for agricultural purposes. This analysis will allow the development of an optimized structural and algorithmic organization for the computerized system. This system is designed to implement effective monitoring and decision support for managing agricultural processes. The research object is existing approaches and methods for organizing monitoring systems in the agricultural sector to collect, transmit, and process measurement data. The research subject is information and communication software and hardware solutions in the field of computerized monitoring for agricultural purposes. Conclusions. It has been substantiated that the development and implementation of conceptual software and hardware solutions in information technology for monitoring soil and climatic parameters when cultivating agricultural crops in open-field conditions are currently a relevant scientific and applied task. The set of requirements for the structural and algorithmic organization of the IoT technology for soil and climatic monitoring has been substantiated. An analysis and selection of technologies on which the investigated hardware and software solution will be based have been carried out. The overall and detailed structural and algorithmic organization of the investigated IoT system for agrotechnical monitoring has been developed, and priority directions for further research have been established.

A New Framework for Smart Doors Using mmWave Radar and Camera-Based Face Detection and Recognition Techniques.

By integrating IoT technology, smart door locks can provide greater convenience, security, and remote access. This paper presents a novel framework for smart doors that combines face detection and recognition techniques based on mmWave radar and camera sensors. The proposed framework aims to improve the accuracy and some security aspects arising from some limitations of the camera, such as overlapping and lighting conditions. By integrating mmWave radar and camera-based face detection and recognition algorithms, the system can accurately detect and identify people approaching the door, providing seamless and secure access. This framework includes four key components: person detection based on mmWave radar, camera preparation and integration, person identification, and door lock control. The experiments show that the framework can be useful for a smart home.

Three-Party Evolutionary Game Analysis of IoT Platform Knowledge Hiding Under Organization Participation from the Perspective of Stakeholders

The 21st century is an era of rapid development of high-tech industry. Through continuous collection and sharing of data, IoT technology connected by things has penetrated into every aspect of human life. Modern organizations find that they increasingly rely on knowledge and information sharing and interconnection to enhance their innovation and development capabilities. Therefore, this paper studies the strategic decision-making of knowledge sharing among employees on the IoT platform drawing on evolutionary game theory, this paper constructs a three-party game model composed of “organization-knowledge sharers-knowledge seekers” from the perspective of stakeholders, and discusses the strategic choice of organization and employee behavior under the dynamic decision mechanism and when the game reaches equilibrium and stability. Moreover, this paper uses MATLAB 2016a to simulate the model. The results show that under the premise of higher organizational rewards, synergistic benefits, high-shared extra income, knowledge-sharing preferences, incentive preferences of the organization, the system is easier to reach the ideal state. With the smaller cost of sharing and incentive, organization and employees are more willing to be motivators and sharers, while the incentive degree of organization should be controlled within a reasonable range. This paper can provide specific theoretical and practical guidance for the practice of organizational knowledge management.

Implementation of the Internet of Things in the Global Library Environment: Bibliometric Analysis

The relevance of the topic. Even though the potential of IoT in optimizing library processes and creating innovative services is meaningful, we can observe a lack of research focused precisely on the implementation and application of IoT in libraries. Studying IoT in the context of libraries requires an in-depth analysis and a systematic approach to expand the opportunities for developing recommendations and guidelines for library institutions.
 The purpose of the article is to analyze bibliometric data obtained from the Scopus scientometric database concerning the application of Internet of Things technologies in library and information production.
 The methodology of the research includes the methods of analyzing information regarding data obtained from the Scopus database and its generalization.
 Conclusions. The analysis and systematization of data from the Scopus database showed that research focuses on innovative applications of IoT, data security, and library services’ development. The identified trends and dynamics of publications indicate that the role of IoT technologies in the modern library sector is persistently growing. Given the increasing number of publications from 2010 to 2022, a positive trend in the number of scientific studies in this area is expected, especially after the reduction of COVID-19 related quarantine restrictions. These conclusions can serve as a foundation for further research and the development of strategies for implementing IoT in libraries.
 Scientific novelty of the paper is evident because no article containing the analysis of bibliometric data in the sphere of library industry has ever been published. These data were retrieved from the Scopus scientometric database concerning the application of the Internet of Things technologies in libraries worldwide.

Application of YOLOv5 for mask detection on IoT

The combination of the Internet of Things and deep learning technology is usually accompanied by many problems, such as limited bandwidth and computing resources. IoT combined with deep learning often causes system freezes or delays due to limited computing resources. Upgrading the hardware equipment of the IoT system requires a large economic cost, but using a lightweight deep learning model can reduce the consumption of hardware resources to adapt to the actual scene. In this paper, we combine IoT technology and improve a lightweight deep learning model, YOLOv5, to assist people in mask detection, vehicle counting, and target tracking, which does not take up too many computing resources. We deployed the improved YOLOv5 on the server side, and completed the training in the container. The weight file after training was deployed in Docker, and then combined with Kubernates to get the final experimental results. The resulting graph can be displayed by opening a browser at the edge node and entering the relevant IP address. Users can also perform certain operations on the results in the front end of the browser, such as drawing a horizontal line in the road to complete the local vehicle count. These operations are also fed back to the server for interaction with developers. For improved YOLOv5, the recognition speed and accuracy are faster than before. At the same time, compared with the previous version, the model itself requires less storage space and is easier to deploy, making the model easier to implement in the operation of edge nodes. Theoretical analysis and experimental results verify the feasibility and superiority of the proposed method.

Real-Time Air Density Measurement with IoT Integration

This paper presents the design and implementation of an IoT-based air density measurement system that integrates BMP180 and DHT22 sensors with an Arduino Uno microcontroller and ESP8266 Wi-Fi module. The system measures temperature, humidity, and atmospheric pressure to calculate air density in real-time, displaying the results on an LCD screen and transmitting the data to a smartphone app (Blynk) for remote monitoring. The goal of this research is to create a reliable, automated system capable of providing continuous air density measurements without the need for manual intervention. To evaluate the system’s accuracy, data were collected and compared with reference values from the Korea Meteorological Administration (KMA) for August 2023. The comparison revealed that the system produced air density measurements with an average error of less than 0.2%, demonstrating its high level of accuracy and reliability. The system is particularly suited for laboratory environments, where real-time and accurate air density measurements are essential. The use of IoT technology allows for remote data access and continuous monitoring, making the system convenient for various applications, including environmental monitoring and industrial settings where air density plays a crucial role. Future improvements could include sensor calibration enhancements and the integration of additional environmental parameters, such as CO2 levels or particulate matter, to broaden the system’s functionality. Overall, the IoT-based air density measurement system offers a cost-effective and scalable solution for real-time environmental data monitoring.

A Multidimensional Data Collection and Edge Computing Analysis Method

With the development of IoT technology, many dimensions of data are generated in the environment where we live. The study of these data is critical to our understanding of the relationships between people and between people and cities. The core components of IoT technology are sensors and control circuits. However, merging various sensor data and real-time data processing is often a difficult problem, usually related to factors such as coverage, lighting conditions, and accuracy of object detection. Therefore, we firstly propose a wireless transmission hardware architecture for data acquisition mainly based on vision sensors, and at the same time, incorporate some sensors for data calibration to improve the accuracy of data detection. The collected data are fed back to the edge computing platform for fast processing. The edge platform is designed with a lightweight target detection model and data analysis model. Through this multidimensional data collection and analysis, a generalised functional model for public space utilization can be fitted, which enables the calculation of utilization rates for any parameter in public space. The technology improves a technical reference for multi-dimensional data collection and analysis.

Application and Development of Embedded Systems with IoT Components: Aspect of Safety and Reliability

We will present the possibilities of application and development, especially in the field of embedded systems, its interaction with other IoT components, the security aspects of individual components, as well as the domain of their interaction. In embedded systems, we will present new technologies such as fuzzy logic, application possibilities in embedded systems, and machine learning, as application possibilities through the implementation of machine learning. Then we will describe some more examples of the application of fuzzy logic, the automatic control of certain functions in cameras, as well as the defuzzification process, and the possibility of application in security cameras. In embedded systems, we will present the basic aspects of optimization and security, both in everyday applications and in interaction with other components of IoT technologies. The paper shows how security, reliability, and cost estimates affect the implementation phases and the final use of embedded systems, through examples of their application in industry. Security and data protection is shown through the construction of the mentioned devices, their application, but also different encryption methods, permissions, security devices at the network level, as well as implemented IoT technologies. Application examples are focused on the real segment, both in the field of transport, multimedia, design, and in the field of industrial application possibilities.

Blockchain and trusted reputation assessment-based incentive mechanism for healthcare services

Blockchain-based healthcare IoT technology research enhances security for smart healthcare services such as real-time monitoring and remote disease diagnosis. To incentivize positive behavior among participants within a blockchain-based smart healthcare system, existing efforts employ benefit distribution and reputation assessment methods to enhance performance. Yet, there remains a significant gap in multidimensional assessment strategies and consensus improvements in addressing complex healthcare scenarios. In this paper, we propose a blockchain and trusted reputation assessment-based incentive mechanism for healthcare services (BtRaI). BtRaI provides a realistic and comprehensive reputation assessment with feedback to motivate blockchain consensus node participation, thus effectively defending against malicious behavior in the healthcare service system. Specifically, BtRaI first introduces multiple moderation factors for comprehensive multidimensional reputation assessment and credibly records the assessment results on the blockchain. Then, we propose an improved PBFT algorithm, grounded in the reputation assessment, to augment blockchain consensus efficiency. Finally, BtRaI designs a token-based reward and punishment mechanism to motivate honest participation in the blockchain, inhibit potential misbehavior, and promote enhanced service quality in the healthcare system. Theoretical analysis and simulation experiments conducted across various scenarios demonstrate that BtRaI effectively suppresses malicious attacks in healthcare services, improves blockchain node fault tolerance rates, and achieves blockchain transaction processing efficiency within 0.5 s in a 100-node consortium chain. BtRaI’s reputation assessment and token incentive mechanism, characterized by realistic differentiation granularity and change curves, are well-suited for dynamic and complex healthcare service environments.

Opportunities and Advantages of the Ukrainian Technology Market «Smart Home»

. Comfort has always been one of the drivers of progress, forcing people to invent new devices to make life easier. The increase in the number of devices connected to the Internet has triggered an escalation of the IoT revolution. The Internet of Things combines software and hardware capable of tracking and remotely controlling various processes in the areas of human activity: smart transportation, environmental protection, government work, public safety, industry, daily life, education, healthcare, etc. The constant development of IoT technology makes it more intelligent, creative, and convenient. The modern world is constantly transforming due to technological innovations, and one of the most relevant technologies today is the smart home. According to Policy Advice, the global IoT market will reach $520 billion by 2027. Technology has reached a point where people are ready to embrace this lifestyle. In the Ukrainian reality, there are a number of problems that, on the one hand, slow down the growth of the smart home market, and on the other hand, create prospects for development. This paper analyzes the Ukrainian technology market, which will help to better understand how the smart home is becoming an important part of our everyday life and economy, which is extremely important in the context of the development of modern society. The article examines the smart home technology market and its prospects. The opportunities and advantages of the smart home market for Ukraine are considered. The development of this market can have a positive impact on the economy, in particular through the creation of new jobs, increased production efficiency and increased competitiveness in the global market. Given the significant growth in demand for such products, the market is being flooded with offers of smart home solutions, and competition between manufacturers is increasing, which has a positive impact on the range of innovative products. To predict the direction of IoT technology development, let's analyze the facts available to us.

Human activity recognition through deep learning: Leveraging unique and common feature fusion in wearable multi-sensor systems

With the progress in IoT and AI technologies, multi-sensor fusion for human activity recognition (HAR) has garnered considerable attention. As a result of integrating diverse information from different sensors, individuals employ sensors to monitor their daily activities. However, identifying crucial features for classification and assigning suitable weights to sensors is a complex task. On the other side, varied data structures pose challenges in establishing a unified format for the fusion of diverse data. To address these challenges, this paper presents UC Fusion, a method focusing on the fusion of unique and common features in wearable multi-sensor systems for HAR. First, UC Fusion merges the unique feature of each sensor with the common features of all sensors. Second, it tackles the challenge of handling heterogeneous data by unifying the data format through segmentation and dimensional transformation. Extensive experiments on the UCI HAR and WISDM datasets were conducted to evaluate UC Fusion’s performance. The results demonstrate that our proposed method secured an average recognition accuracy of 96.84% and 98.85%. Furthermore, ablation studies were performed on each module of UC Fusion to assess their impact on accuracy, confirming the effectiveness of the proposed method.

AIoT-CitySense: AI and IoT-Driven City-Scale Sensing for Roadside Infrastructure Maintenance

The transformation of cities into smarter and more efficient environments relies on proactive and timely detection and maintenance of city-wide infrastructure, including roadside infrastructure such as road signs and the cleaning of illegally dumped rubbish. Currently, these maintenance tasks rely predominantly on citizen reports or on-site checks by council staff. However, this approach has been shown to be time-consuming and highly costly, resulting in significant delays that negatively impact communities. This paper presents AIoT-CitySense, an AI and IoT-driven city-scale sensing framework, developed and piloted in collaboration with a local government in Australia. AIoT-CitySense has been designed to address the unique requirements of roadside infrastructure maintenance within the local government municipality. A tailored solution of AIoT-CitySense has been deployed on existing waste service trucks that cover a road network of approximately 100 kms in the municipality. Our analysis shows that proactive detection for roadside infrastructure maintenance using our solution reached an impressive 85%, surpassing the timeframes associated with manual reporting processes. AIoT-CitySense can potentially transform various domains, such as efficient detection of potholes and precise line marking for pedestrians. This paper exemplifies the power of leveraging city-wide data using AI and IoT technologies to drive tangible changes and improve the quality of city life.

Dual Axis Solar Tracking of Solar Radiation for Agriculture usage

Energy is one of the important parts of our life. As there is decline in fossil fuels and increasing demand for energy an alternate energy source is required which is renewable energy source like solar, wind etc. So, we use solar panels which trap the energy from the sun and produce electricity, and this energy is used for agriculture purpose like to run water pumps and to meet other energy requirements in agriculture. Due to rotation of earth the stationery solar panel will receive energy only for smaller duration so to overcome this we use dual axis tracking system which rotates solar panel according to direction of sun and helps in producing more solar energy. Agriculture is one of the major contributing sectors to the economy of a country and it requires automation and advanced technology so that it helps farmers in producing more yield and better crops. So, in agriculture continuous monitoring of soil and water level is required so we can automate this which helps the farmers where the device continuously monitors and depending upon the moisture level of the soil the water pumps get on automatically and we can use this for different crops and set threshold depending upon the crop type. And we can also integrate this idea with IOT technology for improvements. By this we create sustainable energy indirectly producing sustainable environment.

Application of IoT Based Renewable Energy For Electric Power Laboratory Campus C In Politeknik Piksi Ganesha

The rapid advancement of technology has increased efficiency in human activities while also escalating electricity consumption, especially with the implementing of the Industry 4.0 revolution in Indonesia. To enhance the use of renewable energy, IoT technology is employed to optimize system performance with real-time data and remote control. In the second-floor laboratory of campus c Piksi Ganesha Polytechnic, there are frequent power outages due to simultaneous use of the lab. The advantage of using this energy is that PLN electrical sources can be replaced using solar panels. This research integrates renewable energy with IoT to improve laboratory electricity usage efficiency. An ESP32-based solar panel is used to collect and control energy data. Successful testing demonstrates the ability of this system, with a 67% utilization of renewable energy. The solar cell requires attention from hardware devices. The integration of renewable energy with Telegram is efficient and can be applied to another system.

A secure blockchain framework for the internet of medical things

AbstractTechnological advancements in the Internet of Medical Things (IoMT) enable medical services to provide incredibly challenging real‐time functions. The proliferation of health sensors has improved patient monitoring, both for patient care and medical purposes, giving professionals more data for early diagnosis and treatment recommendations. Privacy and security are critical considerations for collecting and transferring data from these heterogeneous sensors across the database and the IoT network. This study leverages blockchain technology to improve Electronic Health Record (EHR) privacy and security. This article proposes a novel decentralized architecture using IoT and Blockchain technology for storing EHR and monitoring real‐time patient data. The proposed patient‐centric framework and architecture offer a straightforward solution that fulfills data integrity and anonymity and meets the data interoperability demands. Self‐contained encryption–decryption and primitive cryptographic techniques enhance the system's security. The proposed study models IoT health sensors such as body temperature, pulse rate, spO2, and Electromyogram (EMG) in a blockchain‐based IoT framework. The proposed system has been evaluated to determine that it can process and store Remote Patient Monitoring (RPM) data with encouraging results. The article provides performance, security, and threat analysis to contribute toward a robust, secure, and smart healthcare system using metrics such as latency, throughput, IoT sensor activity, and resource usage. Experimental results present that the proposed method beats the standard healthcare system regarding service quality and patient data monitoring.

IMPLEMENTASI METODE SAW (SIMPLE ADDITIVE WEIGHTING) untuk MENENTUKAN PRIORITAS KEBERSIHAN TOILET SEKOLAH BERBASIS Internet of Things

This research proposes the implementation of the Simple Additive Weighting (SAW) method as an approach to determine priorities for school toilet cleanliness based on IoT. The system integrates temperature, humidity, and ammonia gas sensors as key indicators to measure the cleanliness condition of toilets. The SAW method is employed to calculate the relative weight of each parameter, which is then used to assign priority scores. The system operates by utilizing temperature sensors to identify the toilet's environmental temperature, humidity sensors to measure humidity levels, and ammonia gas sensors to detect ammonia concentration, a crucial indicator of toilet cleanliness. Data from these sensors are collected and processed using the SAW method, enabling the automatic determination of toilet cleanliness priorities. The success of this implementation is tested through simulations and field testing. Experimental results demonstrate that the system is capable of providing priority scores with high accuracy, allowing for more efficient management of toilet cleanliness. Other advantages include the system's ability to provide real-time notifications to relevant parties through the IoT platform, facilitating prompt corrective actions. This research contributes to the development of intelligent solutions for school toilet cleanliness management, integrating IoT technology and the SAW method to provide a measurable and effective approach. With the adoption of this system, it is expected to enhance the quality of school toilet sanitation, support student health, and optimize school facility management.

FROM CONCEPT TO REALITY: UNDERSTANDING THE INTERNET OF THINGS

Despite numerous studies and examples, the phrase “IoT”-Internet of Things continues to be a source of confusion for individuals. The purpose of the research is to give a basic explanation of IoT. Despite the increasing usage of the term, there is currently no accepted definition or understanding of what the Internet of Things actually entails. IoT technology is increasingly expanding into practically all areas of everyday life. Today, more and more companies are starting to introduce a number of IoT-based products and services. We can say that IoT is the merging of the physical and digital worlds through the Internet. The Internet of Things will affect many different domains. Provisions for both the structure’s security and users’ privacy must be included in the regulatory framework. It will also be necessary to take into account any legal obstacles that might prevent the Internet of Things from being fully utilized.