IoT Based Smart Inventory Management System for Kitchen Using Weight Sensors, LDR, LED, Arduino Mega and NodeMCU (ESP8266) Wi-Fi Module with Website and App

Rezwan, Sifat; Ahmed, Wasit; Mahia, Mahrin Alam; Islam, Mohammad Rezaul

doi:10.1109/icaccaf.2018.8776761

Cited by 30 publications

(15 citation statements)

References 7 publications

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“…Chopade and Nighot [25][26][27] worked on kitchen pantry systems that detect the level of food stored on shelves and alert the user whenever it reduced and suggest the nearby stores from where the user can purchase that food item. Journal of Sensors…”

Section: 2mentioning

confidence: 99%

Smart eNose Food Waste Management System

et al. 2021

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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.

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Section: 2mentioning

confidence: 99%

Smart eNose Food Waste Management System

et al. 2021

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“…By basic programming, can build up a Wi-Fi association and characterize input/yield pins as per our requirements, transforming into a web server, cloud and much more. Sensors are connected to the microcontroller board and this sent sensor data to cloud using wi-fi module [8,1].…”

Section: A Microcontrollermentioning

confidence: 99%

“…The expansion of innovation is unpreventable. Each development is made to have helpful effect on human life [1].…”

Section: Introductionmentioning

confidence: 99%

Sensor Based Industrial Kitchen Foodstuffs Monitoring System

Palanisamy¹,

Saranya²

2021

ijcci

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Artificial Intelligence based foodstuff monitoring system is used for inventory management in industrial kitchens, restaurants, canteens, vegetable stores and so on. If the store keeper is not available to monitor the grocery and orders, the process will be risky. The proposed method considers the level estimation detection using ultrasonic sensor and if the container is empty then the information is sent to the store keeper. By this method, the intimation about availability of specific food item can be found and items not available can be ordered for purchasing. The DHT11 sensor is used to monitor the humidity and temperature inside the container, if any of these two is high then the notification will be sent. Decomposed organic items are identified by MQ3 sensor based on detection of alcoholic gas produced by organic items. The sensors data such as grocery level, humidity, temperature and decomposition range of organic items are collected from the corresponding smart container. This data transaction happens via micro controller known as Node MCU. The level of the groceries present, and spoiled organic items can be identified and mail notification can be triggered in the early stage with the help of mobile application called IFTTT.

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“…Rezwan S. ve ark. [1], IoT'ye dayanan, mutfak, ilaç, restoran envanterini yönetmeyi daha verimli ve sorunsuz hale getirecek bir sistem olan akıllı mutfak envanter yönetim sistemi (Smart kitchen inventory management system: SIMS) önermişlerdir. Önerilen sistemi simüle etmek için farklı sensörlerle birleştirilmiş dokuz bölme içeren küçük bir prototip kabin üretmişlerdir (Şekil 1).…”

Section: Envanter Kontrollü Sistemlerunclassified

Akıllı Mutfak İçin Tasarlanmış Sistemler Üzerine Bir Derleme

Küçük¹,

Ekren²

2020

porta

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Günümüzde hızla gelişen teknoloji ile birlikte birçok yenilik de hayatımıza girmiş bulunmaktadır. Bunların başında ise hayatımızı kolaylaştıran çeşitli akıllı sistemler gelmektedir. Yaşamımızın her alanına uyarlanabilen bu sistemlerde amaç hayatı kolaylaştırmanın yanı sıra enerjiyi etkin kullanmaktır. Nesnelerin interneti ile de entegre edilmiş ve iyi tasarlanmış akıllı bir sistem her açıdan kullanıcı konforuna hizmet etmektedir. Her birey ve ortam için uygun nitelikte tasarlanmış çalışmalar yaygın şekilde görülmeye başlanmıştır. Bu çalışmada ise akıllı ev kavramından yola çıkılarak, çeşitli senaryolara dayanarak üretilmiş ve birçok ek sistemle desteklenmiş güncel akıllı mutfak tasarımları incelenmiştir. İncelenen çalışmalarda da görüleceği üzere akıllı olmayan bir sisteme kıyasla enerji, zaman ve konfor gibi öğeler göz önüne alındığında akıllı bir sistemi tercih etmek her zaman daha mantıklı hale gelmiştir.

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IoT Based Smart Inventory Management System for Kitchen Using Weight Sensors, LDR, LED, Arduino Mega and NodeMCU (ESP8266) Wi-Fi Module with Website and App

Cited by 30 publications

References 7 publications

Smart eNose Food Waste Management System

Smart eNose Food Waste Management System

Sensor Based Industrial Kitchen Foodstuffs Monitoring System

Akıllı Mutfak İçin Tasarlanmış Sistemler Üzerine Bir Derleme

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