Jul 2026· 2026 6th International Conference on Electrical, Computer and Energy Technologies (ICECET)· pp. 1-8· 0 citations· 19 references
Abstract
Industry 4.0 is a broad framework that includes many partially overlapping concepts such as smart manufacturing, cloud computing, industrial Internet of Things (IIoT), and smart factory. It relies on technologies such as Internet of Things (IoT), Cyber-Physical Systems (CPS), and Cloud Computing to enhance and streamline industrial processes. This paper focuses on the programming of an IoT-based laboratory-scale, automated, and smart factory using SIEMENS programmable logic controllers (PLCs), along with human machine interfaces (HMIs). The integration of IoT technologies is to achieve three main tasks. Firstly, remote update of the storage, retrieval, and processing of products in the factory by implementing a Radio Frequency Identification (RFID) based tracking system using Node-RED dashboard. Secondly, remote real-time monitoring of the factory by implementing a camera-based surveillance system. Finally, remote assessment of the temperature, humidity, pressure, and air quality of the factory by integrating an environmental sensor. A timed test was conducted to determine the time duration required for one workpiece (product) to complete the entire processing operation. The duration for the entire processing operation of the smart factory from retrieval to final storage is 1 minute and 37 seconds.
Abstract
The Internet of Things (IoT) has emerged as one of the most significant technological advancements in recent years, enabling seamless communication and interaction among physical devices through the Internet. IoT technology has transformed traditional monitoring and control systems by providing real-time data collection, remote accessibility, intelligent decision-making, and automated control mechanisms. The increasing demand for smart environments in sectors such as smart homes, healthcare, agriculture, industrial automation, and smart cities has accelerated the adoption of IoT-based solutions. This dissertation presents the design and implementation of an IoT-based smart system for real-time monitoring and automation using low-cost hardware components, cloud computing platforms, and mobile applications.
The primary objective of this research is to develop an efficient, reliable, and scalable IoT-based monitoring system capable of collecting environmental data, transmitting information to cloud servers, and enabling remote monitoring and automated control. The proposed system integrates NodeMCU ESP8266 as the central processing unit with sensors such as the DHT11 temperature and humidity sensor and the PIR motion sensor. These sensors continuously monitor environmental conditions and transmit the collected data to cloud platforms through wireless communication. ThingSpeak is used as the cloud platform for data storage, visualization, and analysis, while the Blynk mobile application provides users with real-time monitoring and remote control capabilities.
The development process involved hardware configuration, software programming, cloud integration, and system testing. The NodeMCU microcontroller was programmed using Arduino IDE to acquire sensor readings, establish wireless connectivity, and communicate with cloud services. The collected data was uploaded to the cloud platform and displayed through graphical dashboards for real-time observation. Furthermore, automation functionalities were incorporated through relay modules that enable automatic control of connected devices based on predefined threshold values and environmental conditions.
Experimental investigations were conducted to evaluate the performance and effectiveness of the proposed system. The results demonstrated successful real-time monitoring of temperature, humidity, and motion detection parameters. Sensor data was accurately transmitted to the cloud platform and displayed on the mobile application with minimal delay. The automation features successfully triggered control actions whenever predefined conditions were satisfied. The system also demonstrated reliable communication between sensors, cloud servers, and end users, thereby validating the feasibility of the proposed approach.
A comparative analysis between traditional monitoring systems and the proposed IoT-based solution revealed significant improvements in terms of automation, accessibility, data management, operational efficiency, and remote monitoring capabilities. The implementation confirmed that IoT technology can substantially reduce manual intervention, improve response time, and enhance system effectiveness. Despite challenges such as network dependency, security concerns, and sensor limitations, the developed system proved to be a cost-effective and practical solution for intelligent monitoring and automation applications.
Zarreen Fatima, A. Farooqi· International Scientific Jou...· 0 citations
The design and implementation of an Internet of Things (IoT)-based real-time kitchen monitoring and automation system aimed at enhancing safety, efficiency, and intelligent control within kitchen environments is presented.
Simon Usiju Chagwa, P. B. Zirra· Journal of Analytical and Ap...· 0 citations
Detailed analysis of smart manufacturing systems that utilize the IoT and automation technology indicates a high improvement in operational performance, predictive accuracy, and decision-making ability when compared to the traditional manufacturing system.
Aiko Yamamoto· International Journal of Mod...· 0 citations
Modern manufacturing settings cannot function without industrial automation, which has proven crucial for increasing output per worker, decreasing the need for human intervention, and guaranteeing the security of machines. Traditional industrial systems often use isolated components to track machines, identify potential dangers, and manage materials, which leads to inefficient communication, hindered collaboration, and restricted ability to oversee operations remotely. An Internet of Things (IoT) industrial monitoring system that uses an ESP device to select and sort items off a conveyor belt is presented in this study as a solution to these problems. A single integrated platform unifies intelligent material handling and industrial parameter monitoring in the suggested system. When it comes to continual machine safety & health monitoring, an ESP controller serves as the core unit that gathers information gathered by a voltage detector, a temperatures sensor, and fire sensor. A robotic pick-and-place system that uses servos and a conveyor belt work in tandem to automate the sorting and handling of objects. Notifications are sent to an Internet of Things (IoT) online system for remote monitoring when the controller detects abnormal circumstances, for example excessive heat, voltage fluctuation, or fire. The warnings are generated by a buzzer and the LCD display is updated. Connectivity to the internet of things allows for smart automation and adaptable manufacturing processes, including control of the robotic arm and conveyor. To address the needs of smart design, workplace security, and automated pick-and-sort, the suggested system offers a small, affordable, and scalable solution.
S. Pallavi, Sai Sumanth Cherukuru· International Journal of Eng...· 0 citations
The research describes the designing and implementation of a smart home automation system based on the Internet of Things technology, which was developed to increase efficiency, energy saving, and appliance control in a residential setup. Conventional household automation systems require heavy reliance on manual operations, causing energy wastage and inefficiency in operating household appliances. It is intended to build a low-cost but reliable system that will enable the automated control of appliances through the use of environmental sensors data. The components used to design the system include ESP32 microcontroller, PIR Motion sensor, DHT11 temperature sensor, LDR light sensor, relay modules, lighting and fans, power supply using battery, and web-based interface locally. Programming of ESP32 microcontroller was done using Arduino IDE in C/C++, and ESP32 was programmed to run in Access Point mode with the IP address 192.168.4.1, thereby building up a web-based interface locally. Results demonstrate that the system can detect motion, light intensity, and temperature; process the data correctly; and control connected appliances effectively.
A. Udosen, Oluwasemilore Esther Abiola, Christiana Jumoke Daramola· International Journal of Res...· 0 citations
This review examines the application of AI–IoT integrated technologies across multiple industrial domains to identify their strengths, limitations, and recurring challenges and underscores the importance of scalable, secure, and efficient frameworks to ensure the safe and reliable adoption of AI–IoT in the industrial ecosystem.
Asmarani Ahmad Puzi, Ahmad Anwar Zainuddin, Muhammad Afham Anuar et al.· International Journal of Inn...· 0 citations
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