Overview / Usage

1. In India, we never grade the perishables/vegetables during transport for its quality. Hence, we do not have a method to determine the quality and to deliver it accordingly. We PUSH and POP the boxes and deliver the same without intelligence.

2. We propose to monitor the quality real-time during transport, grade the boxes and appropriately to deliver them at places before the food gets spoiled.

3. Also, the driver shall get an ANDROID application where the quality grading can be seen, also, the location updates shall be made available.

4. We can call it internet for transportation.

Methodology / Approach

The data is acquired from perishable boxes in the truck using Temperature (Arduino KY 013 Temperature Sensor) and Humidity Sensor (Arduino HSM 20G Humidity Sensor). As the sensors gives analog output, it becomes inevitable to use the analog to digital converter so as to interface the sensors with Microcontroller unit, NodeMCU (ESP8266-12E) . The data then goes on to the cloud, we have taken Adafruit’s cloud, which is open source service provider. The data from the sensor is transferred to Adafruit’s feed and the data is visualized through Adafruit’s dashboard. Now, the data is transferred to Google sheets using IFTTT’s applets. By storing the data in google sheets, it becomes easier to progress with Data Analytics part. In the google sheets cloud, we are calculating the perishable’s grade using the Optimum temperature for each perishable and grade each vegetable boxes accordingly. Once the grades are assigned to the boxes from Google sheets using JSON, the data is moved into an Android application. At the same time, the Android phone is connected to the internet. In the Android application, it’ll be showing the Box Number, Grade of the Perishables inside and the Location where it is supposed to be delivered making the process complete.

Note: We are building the same with Intel UPSquared Board for indoor Quality monitoring and update. We are also monitoring the food storage unit's food collection centre for the spoilage.

Technologies Used

1. Sensors

2. Data Analytics

3. IFTTT

4. Python

5. NodeMCU

6. Intel UPSquared