IOT Based Smart Kitchen Automation and Monitoring System (Ncastem-2025)
Anand Kumar B1, Sweta Pal2, Pirjade Sabahat Rehan3, Pearl K R Chaudhary4, Mythri C O5
1Department of Computer Science And Engineering, AMC Engineering College, Bangalore, India Email: anand.kumar@amceducation.in
2,3,4,5Department of Computer Science And Engineering, AMC Engineering College, Bangalore
Email: pirjadesabahat@gmail.com
Abstract—This paper proposes a Smart Kitchen Optimization System that integrates Internet of Things (IoT) hardware components with a custom-built software platform to improve kitchen safety, resource efficiency, and user convenience. The hardware built using NodeMCU (ESP82866) for Wi-Fi based data transmission and incorporates multiple sensors including MQ-2 sensor, flame sensor, DHT11/LM35 for temperature and humidity sensing, load cell with HX711 for LPG cylinder weight monitoring, PIR motion sensor for human presence detection, RFID for ingredient identification, GSM module for emergency SMS alerts and relay module to automatically cutoff power in critical situations. The software platform is built on a MERN stack (MongoDB, Express.js, React.js, Node.js) along with Java for the mobile app to be incorporated into the application software for offered services. The interfacing allows the user to view the sensor data with real-time visualization using Chart.js and responsive visualizations via Bootstrapped designs. Sensor data is added through the backend service with the sensor data is gathered and processed, and a history of the data stored within the attached database, as well as simulation of ingredients during cooking activity, displayed through web and mobile interfaces. The application system utilizes intelligent alerting, reports cooking activity, and also offers state of gas and appliances to indicate absence of ingredients, among other layers of usefulness. As cooking and ingredient recommendations, the great part of this system is proposing other appropriate alternative ingredients, when the required ingredient is not available, and keeping the flavour profile based on the recipe. The notion of a safety control and cooking functions (e.g. alternative ingredients) improves the overall usefulness and hence usability of smart kitchen systems. Added benefits include the final solution being scalable, cost-effective, and overall assists towards an intelligence development for situationally and contextually aware domestic spaces. Keywords: Node MCU(ESP8266), Arduino uno, MQ2 Gas Sensor, Load cell, SMART kitchen, Internet of Things (IoT), MERN stack, sensor monitoring, real-time visualization, safety automation, ingredient recommendation.
Keywords— Arduino Uno, Ingredient Recommendation, Internet of Things (IoT), Load Cell, MERN Stack, MQ2 Gas Sensor, Node MCU (ESP8266), Real-Time Visualization, Safety Automation, Sensor Monitoring, Smart Kitchen.
