Smart eNose Food Waste Management System

Abstract

The modern age is an era of fast-growing technology, all thanks to the Internet of Things. The IoT becomes a prime factor of human life. As in this running world, no one cares about the wastage of food. However, this causes environment pollution as well as loss of many lives. A lot of researchers help in this era by introducing some great and beneficial projects. Our work is introducing a new approach by utilizing some low-cost sensors. In this work, Arduino UNO is used as a microcontroller. We use the eNose system that comprises MQ4 and MQ135 to detect gas emission from different food items, i.e., meat, rice, rice and meat, and bread. We collect our data from these food items. The MQ4 sensor detects the CH4 gas while the MQ135 sensor detects CO2 and NH3 in this system. We use a 5 kg strain gauge load cell sensor and HX711 A/D converter as a weight sensor to measure the weight of food being wasted. To ensure the accuracy and efficiency of our system, we first calibrate our sensors as per recommendations to run in the environment with the flow. We collect our data using cooked, uncooked, and rotten food items. To make this system a smart system, we use a machine learning algorithm to predict the food items on the basis of gas emission. The decision tree algorithm was used for training and testing purposes. We use 70 instances of each food item in the dataset. On the rule set, we implement this system working to measure the weight of food wastage and to predict the food item. The Arduino UNO board fetches the sensor data and sends it to the computer system for interpretation and analysis. Then, the machine learning algorithm works to predict the food item. At the end, we get our data of which food item is wasted in what amount in one day. We found 92.65% accuracy in our system. This system helps in reducing the amount of food wastage at home and restaurants as well by the daily report of food wastage in their computer system.

Using IoT and AI to replenish household food supplies: A systematic review

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A Bibliometric Analysis of the Literature on Food Industry Supply Chain Resilience: Investigating Key Contributors and Global Trends

“…For example, logistics and transportation management systems can be used to optimize routes and reduce distance [42]. In addition, food waste tracking systems can be employed to monitor food waste throughout the supply chain, allowing companies to identify opportunities to reduce waste and enhance efficiency [43].…”

Diseño de un prototipo basado en IoT para la medición de residuos orgánicos aprovechables en unidades habitacionales

“…Por otra parte, como transductor de la variable a medir (masa en g o kg), se implementó una celda de carga de 5 kg y el conversor análogo a digital HX711 (AVIA Semiconductor, 2016) este último tiene una resolución de 24 bits, según A. Rasheedha et al (2020) ideal para las pequeñas variaciones de voltaje que entrega la celda de carga cuando está operando (Gull et al, 2021). El consumo es inferior a los 10mA y su comunicación se hace mediante el protocolo I2C a cualquier dispositivo microcontrolado.…”