Implementation Of IoT Research Articles

Training of Trainers 4.0 Industri Kecil Menengah Furnitur Untuk Mendorong Transformasi Digital Dengan Teknologi Internet of Things

The furniture industry in Central Java still faces various challenges, especially in adopting advanced technologies such as the Internet of Things and Industry 4.0. Many furniture SMEs still rely on manual or semi-manual production methods, which result in suboptimal product quality and production efficiency, making it difficult to compete in the global market. To address these challenges, the Community Service Program carried out by the Furniture Industry Business Management Study Program at Polytechnic of Furniture Industry and Wood Processing actively played a role through the Training of Trainers activity. This program aims to provide intensive training on the implementation of IoT and Industry 4.0 technologies to furniture SMEs in Central Java, focusing on developing practical skills and fostering digital transformation. Training of Trainers training involved Furniture Industry Business Management lecturers who possess specialized expertise in Industry 4.0 technologies. The training covered both theoretical and practical aspects, allowing participants to not only understand the concepts but also implement them in their work environments. Evaluation results showed a significant increase in the participants' understanding and skills in applying Industry 4.0 and Internet of Things technologies. A tangible example of the success of this training is PT. AST Indonesia, which successfully implemented Industry 4.0 and Internet of Things technologies in its production processes after participating in the Training of Trainers program. This success is concrete evidence that the training provided by Furniture Industry Business Management can contribute significantly to enhancing the competitiveness of furniture SMEs in the digital era, in line with the vision of "Making Indonesia 4.0.

Development of Pre-paid Energy Meter using Internet of Things

This paper presents an implementation of IoT to develop a pre-paid energy meter system using an IoT prototype for monitoring and controlling energy and power consumption. This system is used for the remote or on-site management of energy and power consumption. The system provides a user interface using Global System for Mobile Communications (GSM) so the user can pay the required price for the desired unit. The system provides a web user interface to monitor energy and power consumption, including the number of units and price. The ultimate goal is to promote a sense of optimization of power usage by letting the user pay before they have access to electricity. The system consists of an energy meter box that is connected to individual load connections. This energy meter box consists of a microcontroller on Arduino, a GSM module, a voltage sensor, and current sensor, and an LCD. The LCDs are the energy and power consumed, the price remaining, and the number of units consumed.

REAL TIME MONITORING OF AIR POLLUTION USING ARTIFICIAL INTELLIGENCE BASED IOT AND NOVEL SARIMA TECHNIQUE IN SIVAKASI - INDIA

<p style="text-align:justify; margin-bottom:13px"><span style="font-size:11pt"><span style="line-height:200%"><span style="font-family:Calibri,sans-serif"><span style="font-size:12.0pt"><span style="line-height:200%"><span style="font-family:"Times New Roman",serif">Air pollution, a harmful or excessive quantity of pollutants from natural sources and human activities, poses risks to human health, the environment, and ecosystems. AI breakthroughs have allowed for the incorporation of technologies into performance indices, resulting in the development of an AI-based air quality system that evaluates water quality in real time using WHO-defined parameters. This article describes the implementation and planning of AI-based IoT for air pollution tracking and forecasting utilizing AI methodologies, as well as a dashboard on the internet for real-time tracking of air pollutants via Google Cloud servers. Air pollutants such as NO<sub>2</sub>, NO<sub>x</sub>, NH<sub>3</sub>, CO, SO<sub>2</sub>, and O<sub>3</sub> are gathered from IoT sensor nodes in Sivakasi, Tamil Nadu, India, utilizing artificial intelligence algorithms. Individual pollutants are forecasted using time series modeling approaches such as Artificial Neural Network (ANN), Naive Bayes Model, k-nearest neighbour (k-NN), Support Vector Machine (SVM), and Seasonal Autoregressive Interated Moving Average (SARIMA). The data from the IoT sensor node is utilized to train the model, resulting in optimal parameters. The derived model parameters are validated using new, previously unknown data for time. The performances of several Time Series models are examined using performance metrics such as Mean Absolute Error (MAE), coefficient of determination (R<sup>2</sup>), and Root Mean Square Error (RMSE). An AI-based algorithm has been flashed in the Raspberry Pi 3. The present air pollution data and anticipated data are monitored throughout a 7days from 10 p.m. to 4 a.m. using a digital dashboard built in an open-source using Google cloud services. Finally comparing to all above AI based algorithms, SARIMA performed well and h+ad a 95% accuracy level. </span></span></span></span></span></span></p>

ZTA-IoT: A Novel Architecture for Zero-Trust in IoT Systems and an Ensuing Usage Control Model

Recently, several researchers motivated the need to integrate Zero Trust (ZT) principles when designing and implementing authentication and authorization systems for IoT. An integrated Zero Trust IoT system comprises the network infrastructure (physical and virtual) and operational policies in place for IoT as a product of a ZT architecture plan. This paper proposes a novel Zero Trust architecture for IoT systems called ZTA-IoT. Additionally, based on different types of interactions between various layers and components in this architecture, we present ZTA-IoT-ACF, an access control framework that recognizes different interactions that need to be controlled in IoT systems. Within this framework, the paper then refines its focus to object-level interactions, i.e., interactions where the target resource is a device (equivalently a thing) or an information file generated or stored by a device. Building on the recently proposed Zero Trust score-based authorization framework (ZT-SAF) we develop the object-level Zero Trust score-based authorization framework for IoT systems, denoted as ZTA-IoT-OL-SAF, to govern access requests in this context. With this machinery in place, we finally develop a novel usage control model for users-to-objects and devices-to-objects interactions, denoted as UCON IoT . We give formal definitions, illustrative use cases, and a proof-of-concept implementation of UCON IoT . This paper is a first step toward establishing a rigorous formally-defined score-based access control framework for Zero Trust IoT systems.

Implementation of audio biostimulators and IOT in STEM learning to enhance the quantity of herbal medicinal plants in Indonesia

This research aims to enhance the contribution of science learning in higher education using a Science, Technology, Engineering and Mathematics (STEM) approach to assist Indonesia’s farmers' herbal medicinal plant communities. The technology implemented in this project-based learning at the Department of Natural Science Education, Yogyakarta State University is the Audio BioStimulator (ABS) and multi-sensors based on the Internet of Things (IoT). These sound waves function to open leaf stomata during photosynthesis optimizing nutrient absorption. On the other hand, IoT comprises a sensor system that measures physical variables encompassing soil composition, air quality, fertiliser concentration, pH levels, pressure and temperature. This system creates optimal conditions to foster the growth of herbal medicinal plants. The research method employed an embedded experimental design which is mixed-methods research. This method is expected to provide more comprehensive analysis results to improve critical and creative thinking skills by applying contextual STEM learning to intensify herbal medicine farming using ABS and IoT technology. These two technologies are strategic for enhancing students’ competency in science practicums in higher education which can also be studied intensively in the science, engineering and mathematics aspects. The STEM approach empowers students to translate acquired knowledge and skills into direct project activities to address the challenges facing farming communities. Its instructional impact lies in elevating critical and creative thinking skills while its consequential bearing manifests in assisting the community to increase the economic status of the herbal medicinal plant farming sector in Indonesia.

Mitigating Frame Cracks in Off-Highway Vehicle: A Combined Approach of Finite Element Analysis and IoT-based Chassis Health Monitoring System

A Heavy-duty cargo truck manufactured by the Chinese company SHACMAN X3000 is designed and analyzed in this paper. Here, this paper developed a Chassis Health Monitoring System (CHMS). The objective of the system is improving the safety measures by combining computational techniques using FEA on static structural and Modal analysis followed by experimental work by implementation of IoT for monitoring and validation purposes. In this paper, for analysis purpose, we selected four critical points based on the survey and underwent the analysis by computational tool. The CHMS consists of a Force sensor, a Flux sensor, and RGB with Arduino, which is to collect and analyze to monitor the frame. The analyzed results give the optimal value in the frame near the critical areas, which results the crack. The CHMS, it a pre-alert system and safe guard the chassis.

IoT Enabled Smart Homes in Tropical Regions as a Means of Sustainable Development

Abstract Internet of Things (IoT) in the context of Smart Homes has been an emerging area of study. IoT technology-enabled provides Integrated and centralized monitoring and control system where the inhabitants can remotely adjust access in the house, temperature and lighting etc., but also functions of the smart TV, refrigerator, oven etc. A step forward to this, Smart 2.0 can be achieved by integrating greeneries maintenance atomization, energy and water conservation, etc., with the IoT technologies to maintain a healthy indoor environment. The study focus on how IoT enabled Smart Homes can contribute, enabling a new era of development and growth aimed at achieving Sustainability. A critical literature review and factors are identified that will align the development catering to the 2030 Agenda for Sustainable Development, 2015 and the UN-Habitat New Urban Agenda, 2016 which are today’s International Agendas aimed at achieving Sustainable Development. Well-planned and well-managed IoT enabled Smart Homes in the context of urbanization, can be a powerful tool for sustainable development for both developing and developed nations. Achievement of SDGs especially, Goal 3, 6, 7 and 11 is impossible without the role of technology. With the proper delivery and implementation of IoT enabled Smart Homes, safeguarding the sustainability of Cities and Communities is possible. IoT in Smart Home keep the power, water, temperature, ventilation systems, solar power, greeneries and waste in check which in turn leads to sustainability. An IoT enabled Smart Home model for Sustainability has been proposed.

IoT Based Temperature Monitoring System Using ESP8266 & Blynk App

This paper addresses the design and implementation of IoT Based Temperature Monitoring System using ESP8266 & Blynk App in. The consists of temperature sensor which can measure the temperature within 1 meter radius & shows the result on OLED Display & Blynk App. This is basically used in hospitals, air conditioners, food processing, etc. We can able to set temperature to maintain a consistent temperature within a medium. We’ll be controlling the temperature via Web dashboard or Blynk App.

Correction: Tsakalidis et al. Design and Implementation of a Versatile OpenHAB IoT Testbed with a Variety of Wireless Interfaces and Sensors. Telecom 2023, 4, 597–610

There was an error in the original publication [...]

IoT-Driven Innovations: A Case Study Experiment and Implications for Industry 5.0

This paper uses a thorough case study experiment to examine the real-world applications of IoT-driven innovations within the context of Industry 5.0. The factory floor has a temperature of 32.5°C, a warehouse humidity of 58%, and a safe pressure level of 102.3 kPa on the manufacturing line, according to an analysis of IoT sensor data. A 5.7% decrease in energy use was made possible by the data-driven strategy, as shown by the office's CO2 levels falling to 450 parts per million. The case study participants, who had a varied range of skills, were instrumental in the implementation of IoT, and the well-organized schedule guaranteed a smooth deployment. Key Industry 5.0 indicators, such as +2% in production efficiency, -5.7% in energy usage, -29% in quality control flaws, and +33.3% in inventory turnover, show significant gains. Key metrics evaluation, data-driven methodology, case study, Industry 5.0, IoT-driven innovations, and revolutionary potential are highlighted by these results.

FEATURES OF THE DEVELOPMENT OF DIGITAL TRANSFORMATION STRATEGIES FOR IMPROVING THE EFFECTIVENESS OF BUSINESS PROCESSES OF COMMERCIAL ENTERPRISES IN UKRAINE

The article analyzes digital transformation strategies, defining their essence, features, advantages, and disadvantages. It examines strategies related to the integration of digital technologies, the use of data analytics, customer orientation, the implementation of IoT, cloud computing, and business process automation. International practices of implementing digital transformation strategies by commercial enterprises are explored, with examples from Walmart, Starbucks, Zappos, John Deere, Airbnb, and AXA Group. Based on the study's results, steps and recommendations are formulated for implementing the synergy of digital transformation strategies by commercial enterprises, which involve the use of data analytics, cloud computing, and robotic process automation (RPA) in business processes. It is determined that a systematic approach to digital transformation ensures control at each stage, avoiding chaotic changes and being key to the successful development of enterprises, improving business process efficiency, customer interaction, and competitiveness.

Digital Tracks: Investigating the Integration of IoT in Modern Public Transport

The use of the Internet of Things in public transportation has fundamentally changed how we engage with and utilize transportation systems. IoT incorporates sensors, communication devices, and data analytics into vehicles and infrastructure to improve the effectiveness, safety, and convenience of public transport for passengers and service providers. This overview discusses the different uses of IoT in public transport such as real-time vehicle tracking, predictive maintenance, intelligent ticketing systems, and passenger safety features. It also evaluates the difficulties and possibilities linked with the widespread implementation of IoT in this sector while providing perspectives on the future development of connected urban mobility.

Design and Implementation of IoT Based Rivers Monitoring System

Water is the most essential element for human life after air, hence the amount and quality of water resources must be monitored by the appropriate government agencies. The goal of this research is to create and implement an IoT‐based rivers monitoring prototype system. Two basic components make up the proposed system: the first component represents the node points, and the second component represents the control point. In order to achieve continuous updates of the information via Internet from the node side, ESP32 with its built‐in Wi‐Fi adapter was utilized. The node should pinpoint three major situations, Normal, High. and Low of river water, and then transfer it using IoT to the control point to take an action depending on conditions at the river. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

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.

Design and Implementation of IoT based PV Integrated Power Monitoring System

The awareness of usage of power and effective utilization of power is based on intelligent decision, which can help the user as well as supplier. In this paper the design and implementation of IOT based PV integrated system is presented. A hardware prototype is developed with PV module connected to boost converter, Arduino Uno controller, ESP 8266 Wi-Fi module, and Thing speak to monitor a real-time power. The Arduino Uno serves as the central controller, gathering data from smart power meters and PV modules for solar energy generation. The collected data is wirelessly delivered to the ThingSpeak, which provides cloud-based storage, data analysis, and visualization. With these users may remotely monitor usage of power, track solar energy generation, and get notifications for energy utilization.

Improvising Safety and Energy Efficiency of IoT based Networks Data Routing

The Internet of Things is also referred to as IoT, outlines the physical object networking which is comprised of sensors, software and other associated technologies and technical tools in order to connect and exchange data over the internet with other devices and systems. The IoT devices range from household to industrial tools. Over the years, one of the most emerging technologies of the 21st century is IoT as it plays a huge role in sophisticated industries to smart application such as cars, household appliances and many more. With the implementation of IoT, people can take an advantage of seamless communication between other people, processes as well as things. Without human intervention, data having key information can be gathered by different means such as computing, cloud, big data, and associated mobile technologies. This paper focuses on making an IOT based network’s data routine safer and more energy efficient.

Implementation of a Real-Time IoT Based Energy Management System

Energy Management System has received a lot of attention from both academia and industries due to the rate of energy consumed by electrical appliances. These industries are faced with inflation in the cost of electrical bills. Therefore, this study presents the design and implementation of a real-time IoT based Energy Management System (EMS) to reduce the inflation in the cost of these electrical bills. The system comprises four (4) basic units namely; the sensing unit, control unit, display unit and switching unit. The sensing unit comprises of two sensors namely; Current Transformer (CT) sensor and voltage sensor which senses and measures the parameters (voltage and current) and sends the parameters to the control unit. This control unit comprises two (2) microcontrollers namely; Arduino Nano and ESP32. The Arduino Nano processes the received data from the sensing unit and sends the processed data to the display unit and ESP32 microcontroller for real-time monitoring. In addition, the ESP32 microcontroller sends the processed data to the cloud. Furthermore, the web-based application receives the measured parameters from the cloud and thus, allowing the user to monitor as well as control the rate of energy consumption of electrical appliances. The experimental results obtained showed that the developed system efficiently monitors and control the rate of energy consumption of the three applied loads (Edison 2.7 bulb, standing fan and phone charger). Hence, reduces the cost of electrical bills consumed by these appliances.

Design and Implementation of IoT Based Smart Lecture Attendance System at Mataram University of Technology

Student attendance is one of the reporting activities that exist in educational institutions. The problem that occurs in educational institutions is that when entering the lecture, many students are late and often absent, which can cause discipline where students often do absenteeism, so lecturers cannot know the number of students who attend accurately. From these problems, a solution is needed to help lecturers recapitulate attendance data. This system uses ESP32 as a data manager, RFID for data reading, and ESP32 to validate student attendance by taking pictures of faces. The data is stored on the web server using ESP32CAM to cover the shortcomings of RFID, which is still card-based, so that it can emphasize the flaws. To simplify the attendance in this study, utilizing the website as an interface to facilitate lecturers in knowing the number of students who are present, late, or absent more efficiently and accurately

Implementation of IoT of an Electric Infant Warmer to Prevent Hypothermia in Newborns

Hypothermia is a drop in body temperature below 36.5°C in newborns. It results in an internal distribution of body heat from the nucleus to the periphery, followed by heat loss greater than metabolic production. Hypothermia is one of the factors predisposing to metabolic disorders, intracranial hemorrhage, respiratory distress, and Necrotizing enterocolitis. Hypothermia problems can be treated with infant warmers. Thus, the need for a infant warmer is considered to improve survival in newborns. This study aims to improve the accuracy of temperature monitoring, increase security, and enable remote monitoring. The temperature sensor of the device is calibrated with comparable devices such as Incubator Analyzer and Thermo hygrometer while the SpO2 sensor is calibrated with Spotlight SpO2 Functional Tester and Thermo hygrometer. Achievement and validation of temperature and oxygen saturation use a calibration comparison tool. The results of the temperature sensor measurements, including air temperature and skin sensor temperature, namely: air temperature error tolerance ≤2°C and skin sensor temperature error tolerance ± 0.5 ° C. All two indicators have the same standard deviation value of ±0.49. The SpO2 indicator reached an error tolerance value of ± 1% O2 with a standard deviation value of ± 0.6-0.9 from six trials. Then the pulse rate indicator obtained an error tolerance of ±5% with a standard deviation value of ±0.6. The smart infant warmer tool provides benefits to avoid excessive heat from the heater and minimize low temperatures that cause hypothermia through the Internet of Things technology. Furthermore, this research can be improved with machine learning technology to increase efficiency and effectiveness in patient treatment.

Design and Implementation of a Versatile OpenHAB IoT Testbed with a Variety of Wireless Interfaces and Sensors

This paper presents the design and implementation of a versatile IoT testbed utilizing the openHAB platform, along with various wireless interfaces, including Z-Wave, ZigBee, Wi-Fi, 4G-LTE (Long-Term Evolution), and IR (Infrared Radiation), and an array of sensors for motion, temperature, luminance, humidity, vibration, UV (ultraviolet), and energy consumption. First, the testbed architecture, setup, basic testing, and collected data results are described. Then, by showcasing a typical day in the laboratory, we illustrate the testbed’s potential through the collection and analysis of data from multiple sensors. The study also explores the capabilities of the openHAB platform, including its robust persistence layer, event management, real-time monitoring, and customization. The significance of the testbed in enhancing data collection methodologies for energy assets and unlocking new possibilities in the realm of IoT technologies is particularly highlighted.