Internet Of Things Technology Research Articles

High-precision, programmable soft wireless robotics for cooling tower cleaning based on Internet of Things technology

Soft robotics with high flexibility & adaptability gain attention for precision tasks in unstructured environments. However, non-contact robotics’ reliance on thermal/optical fields limits stability & stimulus uniformity, resulting in low accuracy, poor scalability, & limited adaptability. This paper introduces a new soft robotic system (PM10B2C robotic) incorporated Internet of Things (IoT) technology and leveraged the Joule thermal effect. The robotic platform is constructed by self-prepared boron nitride nanosheets (BNNS) that exhibit a higher planar area-to-thickness ratio. When the actuation voltage is 8 V, the soft wireless robotic can complete κ = 1.19 cm−1 deformation with deformation efficiency and recovery efficiency of 0.11 cm−1·s−1 and 0.17 cm−1·s−1, and exhibits excellent actuation stability under 500 cycles of testing. Based on the Timoshenko bimetallic constant temperature device model and heat conduction theory, a κmax-U analytical model is constructed to achieve effective prediction of the optimal curvature-low voltage D.C. relationship of PM10B2C robotics. The smart-controlled soft robotic operates continuously and stably within the harsh internal environments and complex spatial configurations of thermal power plant in cooling towers. This design offers novel prospects for developing cleaning robotics tailored for extreme environments and complex spaces in such facilities.

Digital twins and their economically effective using in the logistics field

The characteristics of digital twin technology are given and its use in the field of logistics operations is described. The digitalization of business processes and current concepts of Industry 4.0 and Logistics 4.0, the possibility of using simulation models in the context of improving the technological base of information systems are considered.The need for digitalization in modern Industry 4.0 and Logistics 4.0 is indicated, since currently the most effective way to improve production, speed of transportation, and responsiveness of an organization’s business processes is the introduction of digital technologies, one of which is a digital twin. With its help, it becomes possible to create virtual copies of warehouses, conveyors and even cities. The introduction of this technology provides new opportunities for data analysis and risk-free forecasting of scenarios for the behavior of a digital model, and conducting all kinds of stress tests. When integrated with Internet of Things technology, data can be analyzed in real time and compared with other digitized objects. This approach helps improve the efficiency of both the specific problematic element of the supply chain and the entire system as a whole. It is also possible to improve the safety of workers; the model independently learns from its mistakes using machine learning and displays the results of its activities to people.Digital twins not only show a copy of the required element, but also understand its dynamics, predict behavior, and are also capable of analyzing their own activities.

High performance piezoelectric nanogenerator by fiber microstructure engineering toward self-powered wireless sensing system

Piezoelectric nanogenerator (PENG) with these advantages of low cost, small volume and stable output in extreme environment is constantly required to develop self-powered sensing system in Internet of Things (IoT), which can relieve energy crisis and reduce labor maintenance costs. However, low electrical output of PENG severely restricts its application and has been a key challenge in the development of PENG. To attain high output performance, a new PENG based on core-shell heterostructure of barium titanate(BT)/polyvinylidene fluoride(PVDF) composite fibers coated with BT@Ag was designed for energy harvesting and wireless sensing application. The outputs of PENG with this special structure are enhanced near 3 times than that of PENG based on traditional fibers, benefiting from the enhanced induced-polarization and stress transfer mechanism in PENG, which is confirmed by experimental results and explained by multi-physics simulations. Moreover, the PENG can effectively harvest wind and acoustic energy, which can deliver the high outputs of 107.5 V and 16.18 µA under 12 m/s wind speed, 45.4 V and 6.5 µA under 110 dB sound pressure, respectively. To verify the practicability of the PENG, a whole self-powered wireless sensing system based on the PENG to harvest energy in environment was demonstrated, where the signal of humidity condition of soil can be sensed periodically and transmitted to mobile phone for further analysis. This work provides an effective strategy to boost performance of PENG and further paves a route about advanced self-powered wireless sensing technology in IoT.

Construction of English corpus oral instant translation model based on internet of things and deep learning of information security

In order to improve the security and performance of the oral English instant translation model, this paper optimizes the instant translation model through the Internet of Things (IoT) security technology and deep learning technology. In this paper, the real-time translation model based on deep learning and IoT technology is analyzed in detail to show the application of these two technologies in the real-time translation model, and the related information security issues are discussed. Meanwhile, this paper proposes a method combining deep learning network and IoT technology to further improve the security of instant translation model. The experimental results show that under the optimized model, the parameter upload time is 60 seconds, the aggregation calculation time is 6.5 seconds, and the authentication time is 7.5 seconds. Moreover, the average recognition accuracy of the optimized model reaches 93.1%, and it is superior to the traditional machine translation method in accuracy and real-time, which has wide practical value and application prospects. Therefore, the research has certain reference significance for improving the security of the English corpus oral instant translation model.

Research on Laboratory Construction and Management Based on Internet of Things and Deep Learning

A computer laboratory intelligent management and control system based on Internet of Things technology and deep learning is proposed to address the shortcomings of traditional university laboratory management.The system adopts the main embedded technology, mobile communication technology, wireless sensor technology and database storage technology in the Internet of Things technology, laboratory areas and equipment, identify and collect relevant data, monitor abnormal conditions in real time, and alarm. At the same time, the user is provided with a preview of the experimental content and a demonstration of the results through the handheld client APP. The experimental results show that: when the system is powered by 0.35A current, the total system power is about 3W. The NTC thermistor used has a B value of 3435. Under normal temperature, T2 = 298.15K,R = 10KΩ,R0 = 10KΩ. The current temperature value can be calculated according to the value obtained after the analog-to-digital conversion of the microcontroller. The output frequency of the humidity detection circuit is measured by the single-chip microcomputer, and the current ambient humidity can be obtained by substituting the result into the above formula, that is, when the output frequency dimension of the circuit is 6853Hz, the ambient humidity is 40%. Through the application of this system, the inefficient and extensive manual management method of the computer experimental teaching center is completely solved, so that it can bring more intelligent and efficient services to the teachers and students of the whole school, so as to comprehensively promote the experimental teaching of the school.

Environmental Protection Control System Based on IoT and Deep Learning Intelligent Monitoring Sensors

In order to improve the multi-sensor intelligent control performance of environmental pollution detection, this paper proposes a design model of environmental pollution detection intelligent system based on Internet of Things technology. Firstly, this paper uses ZigBee’s Internet of Things networking technology to design the network of the pollution detection system. Secondly, in order to verify the effectiveness of the environmental pollution detection method, this paper carries out system debugging analysis and simulation test, and uses visual dsp++simulation system to debug the system. The network of ZigBee Internet of Things networking technology is adopted to realize the network design of pollution detection system, and VIX bus technology is adopted to carry out environmental pollution detection data communication and information processing, so as to realize the optimal design of intelligent system of environmental pollution detection system. Finally, the experimental test and analysis were performed. The collection period of environmental pollution data is 10 s and the monitoring time is 22 h. Finally, according to the environmental model and parameters, we determine that the system can accurately detect environmental pollution information, and the results are accurate and reliable.

SCALABILITY AND INTEGRATION CHALLENGES OF IOT SYSTEMS IN KAZAKHSTAN

This article presents an analysis of the current state of development and integration of Internet of Things (IoT) systems in Kazakhstan. The article goes on to describe a number of key projects and initiatives aimed at the digitalization of various sectors, including smart cities, agriculture, energy and healthcare. The principal obstacles confronting IoT systems in Kazakhstan are delineated, including infrastructural constraints, the high power consumption of devices, cybersecurity, equipment incompatibility, data processing challenges, organizational impediments, financial limitations, the dearth of proficient professionals, and regulatory hurdles. For each challenge, potential solutions are proposed, including the development of network infrastructure, the implementation of energy-efficient technologies, the assurance of cybersecurity, the standardization of devices and protocols, the training of skilled professionals and the creation of an enabling environment for investment. An integrated approach to addressing these challenges will ensure the successful development and implementation of IoT technologies in Kazakhstan, thereby contributing to economic growth, increasing the efficiency of various industries and improving the quality of life of the population.

Intelligent Vehicle Auxiliary Handling System Based on the Internet of Things Technology

Intelligent Vehicle Auxiliary Handling System Based on the Internet of Things Technology

The role of internet of things adoption on the sustainability performance of the renewable energy supply chain: A conceptual framework

To effectively integrate clean energy resources into the supply chain (SC) and optimize energy consumption, the digitalization of renewable energy supply chain (RESC) plays a vital role in the future. Nonetheless, society must accept these emerging RE technologies to transition successfully into mainstream energy resources. The Internet of Things (IoT) technology can resolve the challenges facing RESC (solar energy) to achieve sustainable development strategies. This study examines how IoT adoption affects the sustainability of the RESC. The sample size consisted of 175 active companies in the RESC in Iran, and a standard questionnaire is distributed among them using a simple random method. Structural equation modeling was used to investigate the hypothesis. We evaluated the questionnaire's discriminative validity, computed composite reliability, and computed Cronbach's alpha to determine its validity and reliability. The results revealed that our research validates six hypotheses about the relevance between lean and eco-friendly actions, SC integration, performance perceived benefit, expenses, peers and government support, and IoT adoption. The findings also suggest adopting IoT technology as a broad-based strategy to attain sustainability in the energy context. As a result of its transparency, immutability, and security features, IoT presents a viable option for RESC sustainability.

A comprehensive review on smart and sustainable agriculture using IoT technologies

The article provides a comprehensive review of the use of the Internet of Things (IoT) in agriculture, along with its advantages and disadvantages. However, it's important to recognize that IoT holds immense potential for generating new ideas that could drive innovations in modern agriculture and address several challenges faced by farmers today. Applications such as smart irrigation, precision farming, crop and soil tracking, smart greenhouses, supply chain management, livestock monitoring, agricultural drones, pest and disease prevention, and farm machinery are among the areas considered for IoT implementation in agriculture by this paper. These innovative solutions have the potential to revolutionize farming practices, improve efficiency, reduce resource wastage, and ultimately enhance agricultural productivity and sustainability. The analysis examines each application in terms of its utility and outlines measures necessary to enhance its effectiveness. Key considerations include addressing connectivity issues, managing costs, ensuring data security and privacy, scaling solutions appropriately, effectively managing data, and promoting awareness and adoption of IoT tools. Despite these challenges, IoT offers numerous benefits to the agricultural sector. The paper underscores the importance of collaboration among farmers, IoT technology companies, academia, and policymakers to address these issues and fully harness the potential of IoT. To achieve this goal, ongoing research, development, and acceptance of IoT-driven solutions are essential to sustain agriculture as a viable option amidst emerging challenges such as climate change and resource scarcity.

IoT-Based Framework for Implementation of Leaf Color Chart for Nitrogen Monitoring in Crop

Effective nitrogen management is essential in precision agriculture to optimize crop yields and promote environmental sustainability. Conventional techniques for evaluating nitrogen levels, although commonly used, suffer from a lack of accuracy and scalability. This research presents a novel design framework that combines the Leaf Colour Chart (LCC), a well-established agricultural tool for nitrogen evaluation, with modern Internet of Things (IoT) technologies. The proposed system utilizes specialized sensors to gather precise leaf color data, which is subsequently analyzed using cloud-based computer vision techniques to correctly and instantaneously predict nitrogen levels. The framework streamlines data gathering and processing, allowing for accurate nitrogen management. This enables the application of fertilizer to specific areas and minimizes wastage. This article provides an overview of the system architecture, examines the difficulties and resolutions in integrating Internet of Things (IoT) technology in agriculture, and showcases case studies that demonstrate the effectiveness of the framework in practical environments. The incorporation of IoT technology with the Leaf Colour Chart signifies a notable progression in agricultural technology, offering the potential to enhance crop management techniques and support sustainable agriculture endeavors.

Enhancing the Functionality of a Single Burner Electric Cooker through IoT Automation

Single-burner electric cookers are frequently utilized in homes and small kitchens because they offer unmatched convenience and portability. However, they often grapple with challenges such as energy inefficiency and limited temperature control, and in some instances, pose potential hazards ranging from fires to electric shocks. Addressing these issues, this research explores the integration of IoT (Internet of Things) automation as a transformative solution to enhance the overall efficiency of single-burner electric cookers. Through the integration of IoT technology, the electric cooker was automated with programmable timer functionality and precise temperature control and connected to a smart device via a wireless connection. This allows users to remotely manage and control the cooker's operations using a dedicated app. The system includes a microcontroller, temperature sensor, timer module, Wi-Fi module, and a mobile app. Users can input the desired cooking parameters on the app, which are then transmitted to the microcontroller through a Wi-Fi network. The temperature sensor continuously monitors the cooking temperature and sends feedback to the microcontroller, which makes necessary adjustments to maintain the desired temperature. The timer function ensures that the cooking process concludes at the specified time, preventing overcooking or burning of food. This system introduces features such as remote monitoring and control, improved cooking precision, enhanced safety measures, and increased energy efficiency

Systematic Literature Review of IoT Botnet DDOS Attacks and Evaluation of Detection Techniques.

Internet of Things (IoT) technology has become an inevitable part of our daily lives. With the increase in usage of IoT Devices, manufacturers continuously develop IoT technology. However, the security of IoT devices is left behind in those developments due to cost, size, and computational power limitations. Since these IoT devices are connected to the Internet and have low security levels, one of the main risks of these devices is being compromised by malicious malware and becoming part of IoT botnets. IoT botnets are used for launching different types of large-scale attacks including Distributed Denial-of-Service (DDoS) attacks. These attacks are continuously evolving, and researchers have conducted numerous analyses and studies in this area to narrow security vulnerabilities. This paper systematically reviews the prominent literature on IoT botnet DDoS attacks and detection techniques. Architecture IoT botnet DDoS attacks, evaluations of those attacks, and systematically categorized detection techniques are discussed in detail. The paper presents current threats and detection techniques, and some open research questions are recommended for future studies in this field.

Research on Internet of Things based Hand-Pushed Wheel Rangefinder Technology

In order to address the accuracy issues of the hand-pushed wheel rangefinder, this paper proposes a solution that integrates IoT technology and angle sensors into the device to enhance accuracy and informationization level. A wheel rangefinder based on Internet of Things (IoT) technology is designed. The central control device of this system adopts a STM32 microcontroller. The system includes a voltage boosting and dropping circuit, a reset circuit, a gyroscope module, an indicator light module, and a Wireless Fidelity (WiFi) transmission module. The gyroscope module is designed to calculate the actual running distance of the handcart through angle measurement, enabling real-time recording and remote transmission of measurement data. Compared with total stations, rangefinders, and measuring ropes, this system is of good effectiveness and its average error is within 1%. At the same time, it has the capability to save measurement information to the database.

Sustainability and Industry 4.0 in the packaging and printing industry: a diagnostic survey in Poland

Abstract Industry 4.0 (I4.0) became an important paradigm to bridge the gap between technologies and humans. The paper aims to diagnose sustainability performance and I4.0 maturity in Poland’s printing and packaging sector and identify research areas where further actions for improvements are necessary. This article adopts a mixed-method study combining in-depth interviews of eleven heterogeneous enterprises, supported with a quantitative survey on a representative sample of 301 companies. The findings revealed an insignificant correlation from a statistical point of view (0.44) between the adopted I4.0 technologies currently used and sustainable best practices. Internet of Things technologies are more often adopted in the printing industry (27.2 %) than in the packaging industry (14 %). The study concludes that using I4.0 technologies boosts the execution of sustainable practices and/or realising sustainable development practices requires I4.0 technology adoption. The paper clarifies that more in-depth analyses are needed to help achieve sustainable objectives for printing and packaging companies through digital technologies. The methodology is replicable and might be applied in other economies across separate multinational enterprises to influence sustainable digitalised business strategy.

Application and prospects of spatial information technology in CO2 sequestration monitoring

This paper systematically reviews the current applications of various spatial information technologies in CO2 sequestration monitoring, analyzes the challenges faced by spatial information technologies in CO2 sequestration monitoring, and prospects the development of spatial information technologies in CO2 sequestration monitoring. Currently, the spatial information technologies applied in CO2 sequestration monitoring mainly include five categories: eddy covariance method, remote sensing technology, geographic information system, Internet of Things technology, and global navigation satellite system. These technologies are involved in three aspects: monitoring data acquisition, positioning and data transmission, and data management and decision support. Challenges faced by the spatial information technologies in CO2 sequestration monitoring include: selecting spatial information technologies that match different monitoring purposes, different platforms, and different monitoring sites; establishing effective data storage and computing capabilities to cope with the broad sources and large volumes of monitoring data; and promoting collaborative operations by interacting and validating spatial information technologies with mature monitoring technologies. In the future, it is necessary to establish methods and standards for designing spatial information technology monitoring schemes, develop collaborative application methods for cross-scale monitoring technologies, integrate spatial information technologies with artificial intelligence and high-performance computing technologies, and accelerate the application of spatial information technologies in carbon sequestration projects in China.

Emerging technology adoption for sustainable agriculture in India– a pilot study

Agriculture is an extremely important sector in the economic growth of countries. In India, agriculture serves over 70 percent of the country's population and contributes approximately one-third of the country's GDP. Agriculture-related problems have continuously acted as a roadblock to the nation's progress toward its full potential. The only viable solution to this issue is to practice sustainable agriculture, which involves bringing traditional agricultural practices up to date. As a result, the initiative intends to utilise automation and Internet of Things technologies in order to make farming smarter. The main objective of this study is to present outcomes for decision-making for improved productivity, agricultural growth, and sustainability of farms for quality food production and food security. For the purposes of this study, the reference period of the data that will be covered spans from January 2015 to December 2019. The R programming language and the R Studio integrated development environment (IDE) are the tools utilized in the processing and analysis approach. This paper analyzed the underlying factors for the agriculture sector to integrate with emerging technologies. This research study identifies major factors for farmers to adopt new emerging technologies to enhance productivity through improved farming processes. Additionally, it recommends improving infrastructure, expanding internet access to rural areas, and encouraging collaborative platforms to boost agricultural technology innovation and knowledge exchange.

Real-Time Home Energy Management with IoT and Blockchain

As a result of the exponential increase in energy consumption, energy shortages, and augmented energy costs have become a significant problem for households. Solar cells are used in many homes and/or buildings to address these problems. However, managing renewable energy sources in homes can be difficult due to the irregular nature of renewable energy production. Internet of Things (IoT) devices can provide real-time data on energy production and consumption, offering a promising solution to this issue. The current study proposes a framework based on IoT and blockchain technology for home energy management by predicting future energy consumption patterns and optimizing energy use in real time. The blockchain module facilitates peer-to-peer energy trading between renewable energy-generating homeowners and consumers. The proposed framework was tested employing a dataset based on smart homes with solar panels and wind turbines. The results manifest a reduction in energy costs and a possible 30% increase in their traditional gain.

Artificial intelligence and internet of things in manufacturing decision processes

This paper explores the influence of the internet of things (IoT) and artificial intelligence (AI) on the decision-making processes of modern manufacturing systems. With the proliferation of IoT devices and the development of AI technologies, manufacturing companies increasingly leverage these technologies to improve their decision-making abilities. This study aims to investigate the potential benefits, difficulties, and ramifications of integrating IoT and AI in manufacturing systems. The review employs the preferred reporting items for systematic reviews and meta-analyses (PRISMA) method with a systematic mapping process with four research questions. A total of 1282 articles were collected between 2017 and 2023, reviewed in accordance with the inclusion and exclusion criteria, and 66 articles were chosen. The research on IoT and AI technologies influentially affects other research in the production control layer manufacturing area based on the top-ten cited articles. In contrast, the research in this area focused on the operations management layer, specifically manufacturing analytics processes. This paper’s findings contribute to a greater understanding of the impact of IoT and AI on decision-making in modern multi-domain manufacturing systems and provide direction for future research in this field.

Utilizing AI and IoT technologies for identifying risk factors in sports

A dynamic cooperation is poised to redefine the limits of athlete safety and performance optimization in the dynamic field of sports science. A new age in sports analysis is promised by the combination of artificial intelligence (AI) and the internet of things (IoT), one in which data-driven insights not only improve our comprehension of athletic performance but also aid to reduce hazards. This academic work explores the complex interactions between AI and IoT in the context of sports. The IoT and AI integration appear to be a strong mix that has the potential to redefine the standards for athlete safety and performance improvement. This study explores the complex interactions between AI and IoT in the field of sports, emphasizing their combined potential for identifying risk factors in a variety of fields. There is a chance to proactively solve sports-related difficulties by utilizing the data-driven capabilities of IoT and the analytical power of AI, opening the door for better informed tactics and decision-making. Through an exploration of this symbiotic relationship, this paper seeks to underline the transformative potential of these technologies in fostering a safer and more performance-oriented sports environment.