Design and implementation of real-time kitchen monitoring and automation system based on internet of things - Ch Anwar Ul Hassan; Jawaid Iqbal; Muhammad Sufyan Khan; Saddam Hussain; Adnan Akhunzada; Mudabbir Ali; Abdullah Gani; Mueen Uddin; Syed Sajid Ullah (Multidisciplinary Digital Publishing Institute (MDPI), 2022)
Automation can now be found in nearly every industry. However, home automation has yet to reach Pakistan. This paper presents an Internet of Things smart kitchen project that includes automation and monitoring. In this project, a system was developed that automatically detects the kitchen temperature. It also monitors the humidity level in the kitchen. This system includes built-in gas detection sensors that detect any gas leaks in the kitchen and notify the user if the gas pressure in the kitchen exceeds a certain level. This system also allows the user to remotely control appliances such as freezers, ovens, and air conditioners using a mobile phone. The user can control gas levels using their phone with this system. In this paper, the ESP32, DHT11 Sensor, 5 V Relay X 8, and MQ-135 gas sensors create a smart kitchen by controlling the temperature, managing humidity, and detecting gas leakage. The system was built on an Arduino board that is connected to the Internet. The hardware was integrated and programmed using an Arduino, and a user Android application was developed. The project’s goal is to allow any Android smartphone to remotely control devices. This method is commonly used in homes, businesses, and grocery stores. Users will be able to control all of their instruments from anywhere, including switches, fans, and lights. Furthermore, simulation was performed using Matlab2016b on multiple houses. In the simulation, not only was the kitchen considered, but also two, four, and six houses. Each house has two bedrooms, one living room, one guest room, two bathrooms, and one kitchen. The results revealed that using this system will have a scientifically significant impact on electricity consumption and cost. In the case of the houses, the cost was USD 33.32, 32.64, 22.32, and 19.54 for unscheduled, two, four, and six houses, respectively. Thus, it was observed that the cost and power are directly proportional to each other. The results reveal that the proposed solution efficiently reduces the cost as compared to that of unscheduled houses.