Research Article Smart eNose Food Waste Management System Shazmina Gull , Imran Sarwar Bajwa , Waheed Anwar , and Rubina Rashid Department of Computer Science, The Islamia University of Bahawalpur, Bahawalpur, Pakistan Correspondence should be addressed to Imran Sarwar Bajwa; imran.sarwar@iub.edu.pk Received 4 March 2021; Accepted 20 June 2021; Published 22 July 2021 Academic Editor: Roberto Paolesse Copyright © 2021 Shazmina Gull et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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 CH 4 gas while the MQ135 sensor detects CO 2 and NH 3 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. 1. Introduction The IoT encompasses all fields of life and turns the world into a smart world. It works in hospitals, supermarkets, security areas, banks, business, offices, laboratories, restaurants, edu- cational institutions, and home making the world smart and intellectual. As household and restaurant automation is discussed, the main unit of both areas is the kitchen where food is produced, cooked, and served to people to feed them and make them healthy. But the main problem is the wastage of food. Food wastage becomes a threatening problem nowa- days. Around 1.3 billion tons of food is wasted each year that is enough to feed 3 billion hungry people each year at a cost of $990 billion [1]. Just in Pakistan, around 36 million tons of food is wasted each year [2]. Greenhouse gases are emitted at food production time (which makes the 14.1% of emission) while methane gas is produced at the time of food decay [1]. Food production con- sumes water as one apple growth consumes 125 litres of water and one-kilogram beef needs to consume 15,400 litres [3]. And a huge amount of food waste contributes to water waste. According to [3], 3.3 billion tons of CO 2 wasted each year, and 1 tons of food waste reduction can save approxi- mately 4.2 tons of CO 2 [4]. To overcome this problem, IoT can help in monitoring and reducing the waste of food. There is a noteworthy requirement to control, monitor, and management of food wastage. A system is a desideratum to cover the above- mentioned measures. This problem can be handled to IoT, as it bordered every field of life, by using some sensors, actu- ators, and modules. This research helps the chef as well as the home and restaurants to reduce the food wastage using IoT sensors and modules. Electronic nose (eNose) concept comprises several het- erogeneous electrochemical gas sensors that work according to the mechanism of human nose. eNose consists of sensing, Hindawi Journal of Sensors Volume 2021, Article ID 9931228, 13 pages https://doi.org/10.1155/2021/9931228