A comprehensive review of IoT (internet-of-things) based food waste management are described in [14 ][15]. Faccio et al. have developed a bin status monitoring system using various ICTs such as volumetric sensors, RFID, GPRS and GPS [19]. The system is designed with RFID tag at the bin level for identification; the RFID reader attached on the vehicle’s bin hook to keep the scanning distance below 1 m; a programmable microprocessor is installed inside the bin to manage the detection measure of fill level using a volumetric ultrasonic detection sensors, GPRS module in the bins, vehicles and control centers. Other research studies explored [16][17], the integration of a ICTs can estimates the quantity of waste as well as monitor trash bin and collections vehicles. Arebey et al. have developed a bin monitoring system with RFID, camera, GPS, GIS and GPRS [14 ].
The authors Muthukkumaran et al. have proposed a soiled waste disposal system using mobile ad-hoc networks [16]. The paper presents a model waste collection of bins, distributed in a highly densely populated city in India. it forms a dynamic multi-hop network that can provide real time information to municipal authorities. The system is support to monitor online and visualize the status of the bind for further use: due to a capacity sensors and ad-hoc transceivers embedded in the bin. In Asimakopoulos el al, authors developed a system collect bin fill level information along with their identify [17]. The system have ultrasonic sensor and active RFID tag on the bins called filed unit and RFID reader installed in any approved personal or installed in a vehicle of existing organization transportation system called mobile sink. The above mentioned system have several limitation that raise barrier to implement an efficient and intelligent waste management. Such limitation include partial system design, lacking enough data, expensive network structure etc. More importantly, none of the studies analyze food wastage and management in university hostel mess in developing country. This paper aims to contribute to an understanding of how technologies such as Internet of things can promote ecological awareness and environmentally sustainable lifestyle of students in Indian University Hostel Mess scenario.
A. Working of the system When user comes to take his/her meal, he picks his/her mess-card and drops in the box. The box, fitted with IR sensor, senses the drop and records the value. This value is then sent to the central storage if it is connected to the network, or else stored locally to allow batched updates when network comes up. The LED matrix, which is hung inside the mess, displays the food waste statistics and the updated count. The updated count is pulled from the central data store. When the user is done with his/her meal, he/she throws the left food in the bin which is kept on top of the weight mat.
This weight mat records the weight and stores locally or send it to the common storage. The web portal updates every N seconds, N being configurable parameter, and shows the current waste statistics and people count. Alongside, the LED display updates the weight numbers. When the waste bin is full, the mess worker can remove the bin and replace it with the new one. After the new bin is placed on the weight mat, it automatically adjusts to zero, to nullify the weight of the bin. This auto-calibration of the weight mat takes five-seconds which is again a configurable parameter.
B. Communication The internal communication between the sub-systems happens serially. The Arduino and Raspberry are connected by a USB cable. The communication between the modules happens implicitly via TCP/IP. Each module is connected to the WiFi hot spot via a Wi-Fi dongle.
C. Food Waste Portal 1) Online Food Waste Graph This part of the portal shows the live feed of food being wasted by the students in the selected hostel, as shown in Fig 3 (a), (b) and (c). The portal also shows the current count of the people who took and are taking their meals. The feed updates every 3-seconds. This part of the portal digs history data to show the trend of food wasted and the number of people who had contributed to the waste. The statistics are daily and week wise. Code Shoppy
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