Papers by Keyword: Internet of Things (IOT)

Abstract: The security issues and problems surrounding the Internet of Things (IoT) and the Internet of Vehicles (IoV) are thoroughly examined in this article. It draws attention to the dangers of intra-vehicle attacks and the necessity of strong security measures. Examining vulnerabilities in both V2I and V2C contexts, the article highlights the risks that individual hackers face due to their global accessibility. It also covers the difficulties that cybersecurity faces from the rise of machine hackers that use AI and big data analytics. The notion of Heterogeneous IoT is presented, which is a promising field of study with a wide range of applications. The article discusses the difficulties that come with managing protocol proliferation, integrating new technologies, and resolving networking issues in the context of the larger Internet of Things. It is emphasized how crucial trust, security, and privacy are to the success of IoT systems. The systematic review approach used in the research adheres to the PRISMA framework and the Cochrane procedure. Finally, it offers design suggestions and future research directions based on expert analysis conclusions. The study highlights the necessity of taking preventative action to lessen dangers associated with IoV and IoT, offering insightful information about the status of IoT research now and opening the door for future security improvements.

Abstract: The need for effective security in residential landscapes and the reduction of energy consumption in connection with home management activities have led to a growing interest in the field of smart home technology. Smart home is an emerging field of technology transforming how people live and interact with their homes. This research develops a smart home automation system with a microcontroller to enhance energy efficiency, safety, and convenience through wireless control of household appliance operations. The system employs two modes of control: manual and automatic. The manual mode offers control and monitoring capabilities through a web application, accessible globally. The automatic mode provides security alerts and intelligent appliance control, minimizing the need for human intervention. The effectiveness of integrating a microcontroller with various sensors and relays for home automation is demonstrated, with a Digital Humidity and Temperature (DHT11) sensor and a Metal Oxide Semiconductor (MQ-5) gas sensor performing reliably with an accuracy rate of nearly 90%, and the light-dependent resistor (LDR) achieving a success rate of over 89%. The energy saving and safety achieved by applying the developed smart home automation system in this study demonstrate the viability of microcontroller-based smart home solutions

Abstract: Overheating have been attributed to the primary problem of continuous running induction motor in the industry. Star-delta control panels are equipped with protection devices against overcurrent and under/over-voltage but are not sufficient for protection against other temperature-producing fault conditions. This study aims to develop and integrate an IoT-based non-intrusive temperature monitoring and control system into a three-phase 30 h.p induction motor controlled by a star-delta panel. A two-stage temperature threshold limit for monitoring and control was setup at 45⁰ C, 60⁰ C below the 85⁰ C maximum operating temperature rating on the motor nameplate. The data entry collected for the two stages are 314 and 88 data points respectively. The results obtained for the two-stage setup showed that the normal operating temperature range between 30⁰ C to 40⁰ C for most of the operating time duration of the induction motor. Temperature anomalies of 45.5⁰ C and 85⁰ C were recorded for the first and second stage setup respectively. Shutdown of the induction motor was recorded for the first stage but not for the second stage which shows that the designed system responds differently to gradual and sudden temperature increase.

Abstract: Heart diseases are one of the leading causes of death worldwide. Therefore, there is the need for a device that can track the heart performance to provide insights on those conditions such as abnormal heart rates which require urgent medical attention and can result in loss of life. This work developed an internet of things (IoT) based heart rate monitoring system. The key components of the system developed include a pulse sensor (SEN-11574), an arduino uno microcontroller, a liquid crystal display (LCD) module, ESP-8266 Wi-Fi module, 18650 batteries and light emitting diodes (LEDs). Using appropriate design models and relevant mathematical algorithms, circuit designs were accomplished with a microcontroller as the central component. A wireless data transmission unit was created using ESP-8266 Wi-Fi module and Thingspeak platform. Performance test was carried out on each of the subunits of the developed system. Heart rate measurement test was conducted on thirty (30) people and compared with the measurements from an existing heart rate monitor (Apple watch series 7) to determine the reading error of the device. The results of the performance test showed that the developed system operated as intended. The device’s reading error was 3.11% for readings obtained while at rest and 3.89% for readings obtained after exercise. The test results also showed that there was unusual rising of the pulse rate after exercise; causing random beat per minute values. The developed system could be deployed for remote health monitoring applications in personal residences, hospitals, health centres and rural areas.

Abstract: This paper presents the development and testing of a smart farming monitoring system utilizing Internet of Things (IoT) and Android technologies to support precision farming practices in Aceh. The system integrates multiple sensors, including DHT11 for temperature and humidity measurement, and soil moisture sensors, all controlled by ESP32 microcontrollers. These components wirelessly transmit real-time data to an Android application, allowing farmers to monitor environmental conditions on their farms remotely. The system was tested at the Universitas Teuku Umar (UTU) farm, where sensor accuracy was validated by comparing the results with external instruments. Linear regression analysis was applied to assess the correlation between sensor data and the external measurements, yielding strong correlations and confirming system reliability. The results demonstrate that the IoT-based monitoring system provides precise and real-time environmental data, offering a valuable tool for decision-making in precision farming. Future directions for the system include expanding its functionalities by integrating additional sensors, improving the Android interface, and exploring predictive analytics through machine learning.

Abstract: Lagoons have a great importance for society, and activities such as fishing or tourism are essential for these areas, for this reason it is important to have a monitoring system in terms of water quality. The central axis of this project was the design and implementation of a sensor network based on the Internet of Things, collecting data using an ESP32 and the Thingspeak platform for data visualization and storage. Data is analyzed using MATLAB, allowing to obtain an estimation of the water quality index of Laguna Jucutuma indicating an average rating of 40, as well as using Machine Learning techniques to obtain a models with an error margin below 3%.

Abstract: This paper presents the design and development of a biomimetic robot utilizing peristaltic locomotion as a method of movement. Inspired by nature, the robot addresses key limitations encountered in conventional robotic systems, such as imbalance affecting the center of mass and restricted adaptability to complex terrains. Integration of Internet of Things (IoT) technology enables real-time data collection, contributing to enhanced performance and efficiency across diverse environments. The utilization of advanced 3D printing techniques facilitates rapid prototyping and customization of robot components. Experimental evaluation demonstrates the effectiveness of the biomimetic approach, highlighting its potential for applications in exploration, disaster response, and healthcare. Analysis of results informs future research directions, focusing on further optimization and integration of emerging technologies to advance robotic capabilities.

Abstract: Sterilization is a crucial process in healthcare. The environment in which it is performed plays a critical role and any change in temperature and humidity of the environment can compromise the process. In addition, the water quality is also fundamental since its contamination and hardness can cause high impact damage to surgical material and medical equipment. It is difficult for public hospitals in Honduras to control these processes, environments, and water, possibly due to factors such as limited budgets or lack of knowledge of international guidelines. It is proposed to develop a monitoring system capable of measuring environmental and water quality parameters through the implementation of IoT for sterilization units. A vast literature review and the support provided by experts in the field allowed to establish the success criteria for the development of the prototype. The V methodology was used for the mechatronic design to obtain a complete product. By means of experimentation and finally field tests were carried out to determine the components that would integrate the system and the validation of their measurements. A monitoring system was developed to measure relative humidity, temperature, dust particles and total dissolved solids in the water. These measurements were displayed on a web based Ubidots dashboard for data visualization, storage, and export. Once the measurements were obtained, a comparison with international standards was carried out to demonstrate the importance of environmental monitoring in this area.

Abstract: This paper discusses the feasibility of geothermal power as a sustainable solution within the agri-food chain focusing on relational to global decarbonization plans. As the world shifts focus towards sourcing Renewable energy for minimal emission of greenhouse gases. Geothermal energy is receiving a lot of attention for its reliability. The Geotto system, which was piloted in the Eburru community of Kenya, showed how geothermal energy – IoT – AI interaction could be utilized in agricultural economies to the optimal level. The project of developing locally-owned incubators powered by geothermal energies helped to increase the hatch ratios as well as the energy, but not the fossil fuel consumption. The cross-sectional utilization of this resource in, for instance, crop drying, greenhouses, and fish farming was discussed as a prospect. Some of the challenges that were observed in Geotto’s case are technical barriers and the opposition to the adoption of new technology by the public and relevant authorities. The Geotto team tackled these problems in cooperation with the community and local government. From this pilot study, it is evident that geothermal power holds promise and value to be pursued as a long-term investment in the pursuit of higher food productivity with less pollution in addition to aiding the case for decarbonization. The pilot findings indicate that the kind of systems being implemented can likely be extended to other agricultural segments to support grassroots initiatives and strengthen world economies.

Abstract: Integrating the Internet of Things (IoT) in advanced manufacturing, known as Industry 4.0, has revolutionized traditional manufacturing processes by introducing a network of interconnected devices, sensors, and systems. This paper examines the various uses of IoT in advanced manufacturing, emphasizing its role in raising productivity, sustainability, and efficiency throughout the industrial spectrum. Predictive maintenance, where real-time data from machinery sensors permits the anticipation of equipment breakdowns, supports proactive maintenance plans, and limits costly downtime, is a critical use of IoT in manufacturing. An in-depth discussion of the ability of IoT-driven automation to optimize production processes is provided in this study. Adaptive and responsive manufacturing systems that can lower waste, increase energy efficiency, and dynamically adjust to variations in demand are made possible. Optimization of the supply chain is yet another crucial area where IoT technology provides revolutionary advantages. Manufacturers can obtain real-time visibility into the movement and status of completed goods and raw materials by deploying IoT-enabled devices. This can result in shorter lead times, enhanced inventory management, and overall supply chain efficiency. The study examines IoT's function in quality control and monitoring, highlighting how IoT-enabled sensors and cameras support waste reduction, real-time quality evaluation, and defect reduction. The paper also introduces the notion of collaborating robots, or Cobots, and digital twins, demonstrating how the Internet of Things (IoT) builds digital twins of physical assets and processes for real-time monitoring and analysis. Furthermore, the IoT-enabled collaborative nature of Cobots allows for smooth communication between human workers and robotic systems. This study concludes by offering a thorough review of the various uses of IoT in advanced manufacturing and highlighting how it is changing conventional manufacturing paradigms into flexible, effective, and sustainable ecosystems. The offered insights emphasize how crucial it is to adopt IoT technology to maintain resilience and competitiveness in the quickly changing field of advanced manufacturing.