The customer is a socio environmental enterprise in India with experience in waste management and resource recovery. The company handles waste from various sources such as MNC’s Tech Parks, residential communities and other bulk waste generating organizations.
The company handles waste from various sources such as MNC’s Tech Parks, residential communities and other bulk waste generating organizations. Each waste collected is weighed before and after segregation.
After segregation, the items are compressed using a banding process post which they are weighed again before it reaches the landfill. All the weight is logged manually for reporting purpose.
To ensure effective process management, accurate data collection and efficient reporting the company reached out to Thingstel to automate this manual work.
The customer wanted a device that would capture data on the press of a button from the weighing scale over RS232 serial port. This data is then pushed to the cloud for further processing and analysis. Customer wanted two unique solutions, one that would collect the data using wireless technology and one that would connect directly to the internet over an ethernet cable. Further, the customer wanted it to be a cost-efficient offering to make the deployment feasible.
Thingstel proposed two solutions for the requirement. One being a LoRaWAN based RS232 Controller that would provide a wireless option. The RS232 controller would be hardwired to the weighing scale and would communicate with a central gateway over LoRaWAN frequency. This solution enables users to battery power the node device which was a central ask to maintain the solution mobile.
The second offering was a Raspberry Pi based device that would fetch the data and store it locally. At set interval, the device would then transmit the data to the cloud over a secure MQTT connectivity. This solution enables for a store and forward option that is essential during internet outage.
Thingstel platform offers visualization of the data in real time as well as maintain timeseries records for historical data access. Cumulative values are then shown for the weighing scale the values are collected from and as a secondary filter the location.
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