Internet of Things (IoT) Based Real-Time Kitchen Monitoring System

Design and Implementation of an IOT-Based Smart System for Real-Time Monitoring and Automation

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.

Smart Campus Air Quality Monitoring: A Real-Time IoT Solution with React Native and Firebase Integration

Findings indicate that the proposed framework serves as an innovative prototype for Smart Health management within higher education institutions, aligned with the global Smart Campus paradigm.

An IoT-based Real-Time Health Monitoring System for Industrial Machines using ESP32 and Cloud-based Automated Shutdown

Industrial machinery operating in manufacturing and process environments is frequently subjected to adverse operating conditions such as excessive temperature rise, abnormal current consumption, and mechanical vibrations, which may lead to performance degradation, unexpected failures, production losses, and safety hazards. To address these challenges, this paper presents the design and implementation of an Internet of Things (IoT)-enabled real-time machine health monitoring and protection system based on the ESP32 microcontroller platform. The proposed system integrates a DHT11 sensor for temperature and humidity monitoring, an ACS712 Hall-effect sensor for current measurement, and an MPU9250 inertial measurement unit (IMU) for vibration analysis. Sensor data are continuously acquired, processed, and transmitted through Wi-Fi to a cloud-based Firebase Realtime Database, enabling remote access and centralized monitoring. A responsive web dashboard hosted on GitHub Pages provides real-time visualization of machine operating parameters, status indicators, and fault notifications. To enhance operational safety and equipment reliability, threshold-based fault detection algorithms are implemented to identify abnormal operating conditions. When predefined critical limits are exceeded, the ESP32 automatically initiates protective actions by disconnecting the machine through a relay module, activating a visual alarm, and updating the fault status on the cloud platform. The dashboard additionally supports bidirectional communication, allowing authorized operators to remotely restart the machine, while a local push-button interface enables manual system recovery. Furthermore, the developed platform incorporates a browser-based logging mechanism that records timestamped sensor measurements, machine status transitions, fault events, and downloadable CSV trend data for maintenance analysis and performance evaluation. Experimental validation demonstrates reliable real-time monitoring with a data refresh interval of approximately 3 s, accurate threshold-based fault detection, dependable cloud connectivity, and effective remote supervisory control. The proposed solution offers a low-cost, scalable, and practical framework for predictive maintenance and industrial equipment condition monitoring in smart manufacturing environments.

SISTEM MONITORING

IoT-based Smart Home Automation with Adaptive Environmental Control and Energy Monitoring

The rapid advancement of the Internet of Things (IoT) has enabled the development of intelligent systems that enhance automation, energy efficiency, and security in modern homes. The design and implementation of this paper are presented. A smart home automation system based on the Arduino, an IoT system. R4 WiFi microcontroller. The system measures the varying environmental parameters of the temperature, humidity and light intensity in the ambient environment with the help of DHT11 and LDR sensors. The system works out the concepts of regulating the conditions inside with the help of the measures of the fans speed regulation with the help of the Pulse Width Modulation (PWM) with the L298N motor driver and with the capabilities of the regulating the brightness of the lights by means of the adaptive dimming technique. Besides automating the environment it is also possible to add an ACS712 current sensor to the system to measure the real-time energy consumption and send the information to the Arduino IoT Cloud to be monitored remotely. The integration of an IR sensor to identify motion, a smoke sensor to detect fire hazards and a solenoid door lock with a relay module is used to enhance the security features. The LED matrix built-in gives immediate visual indication on the system status. The proposed system will provide an economical and scalable system to current smart home applications by integrating environmental control, energy monitoring, and security functionality into one platform.

IoT-Based Smart Sensor Network for Adventure Park Safety and Management

This paper explores and integrates various sensors and Internet of Things technology within a park environment for the empowerment of environmental and weather monitoring, efficient lighting, security, and surveillance monitoring. This empowerment is incorporated with sensors to monitor things like air quality, temperature, water level, and even foot traffic to optimize the park’s functionality and enhance the visitor experience. Microprocessor-based Arduino, ESP32, and ESP8266 controllers are the key processing units of the sensor network. The Internet of Things technology enhances efficiency reduces costs, improves decision-making, and enhances the quality of life in the park. Visitors can use the collected data from cloud servers through the IoT platform. A mobile application often allows users to monitor the information passing by the IoT platform via the cloud. By building digital platforms into Smart Park, planning events and engaging with visitors becomes much easier in a secure environment. In addition, the design of Adventure Park focuses on developing environmental preservation with green technology like solar-powered lights and water conservation. This makes the park sustainable and sets an example for environmentally conscious urban development. The prototype model is created and provided for validation.