Submit your paper : editorIJETjournal@gmail.com Paper Title : EDIBILITY DETECTION USING IOT ISSN : 2395-1303 Year of Publication : 2022 10.5281/zenodo.7348040 MLA Style: - Mohammed Imram SK, Meda Praneetha, Kolipaka Gayathri, Malyala Sai Shreya EDIBILITY DETECTION USING IOT , Volume 8 - Issue 6 November - December 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org APA Style: - Mohammed Imram SK, Meda Praneetha, Kolipaka Gayathri, Malyala Sai Shreya EDIBILITY DETECTION USING IOT , Volume 8 - Issue 6 November - December 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org Abstract In today's world, food deterioration is a serious issue in the modern world since eating rotten food can have negative effects on consumers. to keep the food stored in a proper environment and to limit the rate of breakdown. There are different factors that affect the rate of food decomposition include temperature, bacteria, humidity, and bacteria are important determinants of the rate of food decomposition.. The device aims at using the right sensors to identify rotten food and keeping an eye on gases emitted by the specific food item. The internet of things uses sensors for scent, humidity, and temperature to deliver alerts in synchrony with one another so that the proper action can be performed. This is widely used in the food industry, where food detection is currently done by hand and automatically. So, in this IoT paper,.In order to track and control the temperature and humidity of the storage environment, we will construct a food monitoring device utilising a DHT11 sensor and an Arduino controller. The DHT11 sensor module is used to measure temperature and humidity, while the MQ4 gas sensor is utilised to detect the state of the food. Module is used. In the future, if needed we can also use a IoT based weight sensor to also monitor the food quantity in the storage area. Reference 1 Genovese, Maria & Zia, Jasim & Fragouli, Despina. (2021). Natural and Biocompatible Optical Indicators for Food Spoilage Detection. 10.1002/9783527820078.ch14 2 Etebari Alamdari, Navid & Aksoy, Burak & Yildirim Aksoy, Mediha & Beck, Benjamin & Jiang, Zhihua. (2021). A novel paper-based and pH-sensitive intelligent detector in meat and seafood packaging. Talanta. 224. 121913. 10.1016/j.talanta.2020.121913. 3 Khan, Suliman & Xiaobo, Z & Ilyas, Muhammad & Rahman, Khalil & Khan, R & Shahid, K & Ahmad, A & Akbar, H & Ahmad, T & Zafar, Z & Iqbal, A & Boateng, R & Maqbool, B & Harlioglu, Muzaffer & Jamil, M. (2021). Fraud Food and Food Spoilage Detection by Non-Destructive Technologies. Annals of the Romanian Society for Cell Biology. 25. 1389-1405. 4 Megalingam, Rajesh Kannan & Sree, Gadde & Reddy, Monika & Krishna, Inti & Suriya, L.U.. (2019). Food Spoilage Detection Using Convolutional Neural Networks and K Means Clustering. 488-493. 10.1109/RDCAPE47089.2019.8979114. 5 Sonwani, Ekta & Bansal, Urvashi & Alroobaea, Roobaea & Baqasah, Abdullah & Hedabou, Mustapha. (2022). An Artificial Intelligence Approach Toward Food Spoilage Detection and Analysis. Frontiers in Public Health. 9. 10.3389/fpubh.2021.816226. 6 Fang, Sun. (2018). Design of Intelligent Detection System for Food Spoilage. 190- 194. 10.1109/ICICTA.2018.00050. 7 Böhme, Karola & Cremonesi, Paola & Severgnini, M & Villa, Tom & Fernández-No, Ic & Barros-Velázquez, Jorge & Castiglioni, Bianca & Calo-Mata, Pilar. (2014). Detection of Food Spoilage and Pathogenic Bacteria Based on Ligation Detection Reaction Coupled to Flow-Through Hybridization on Membranes. BioMed research international. 2014. 156323. 10.1155/2014/156323. 8 Sonwani, Ekta & Bansal, Urvashi & Alroobaea, Roobaea & Baqasah, Abdullah & Hedabou, Mustapha. (2022). An Artificial Intelligence Approach Toward Food Spoilage Detection and Analysis. Frontiers in Public Health. 9. 10.3389/fpubh.2021.816226. 9 Mohammadi, Zahra & Jafari, Seid. (2020). Detection of food spoilage and adulteration by novel nanomaterial-based sensors. Advances in Colloid and Interface Science. 286. 102297. 10.1016/j.cis.2020.102297. 10 Oliveira, Idjane & Junior, Alberto & Andrade, Cesar & Oliveira, Maria. (2019). Biosensors for early detection of fungi spoilage and toxigenic and mycotoxins in food. Current Opinion in Food Science. 29. 10.1016/j.cofs.2019.08.004. 11 Khan, Suliman & Xiaobo, Zou. (2021). Fraud Food and Food Spoilage Detection by Non- Destructive Technologies. Annals of the Romanian Society for Cell Biology. 25. 17. 12 Pinu, Farhana. (2016). Early detection of food pathogens and food spoilage microorganisms: Application of metabolomics. Trends in Food Science & Technology. 10.1016/j.tifs.2016.05.018. Keywords — Temperature, Humidity, Smell, Internet of Things, Food Spoilage, Edibility Detection, Arduino UNO, DHT11 sensor, GSM modem, MQ4 Gas sensor. |