Design and implementation of an intelligent waste garbage can with LoRaWAN and object recognition

Context

In many cities and municipalities, waste disposal has so far been carried out according to rigid schedules, regardless of whether the garbage cans actually need to be emptied. This leads either to unnecessary expense or to overfilled garbage cans causing littering that detracts from the cityscape and causes environmental damage. An intelligent waste garbage can that precisely records its fill level and only requests emptying when it is actually necessary could enable waste to be disposed of in line with demand. Especially in combination with automated waste disposal vehicles, this can increase efficiency, conserve resources and significantly improve waste disposal in cities.

As part of this master's thesis, an intelligent waste garbage can is to be developed in the city of Rastatt that is able to monitor its fill level and send information via LoRaWAN (Long Range Wide Area Network) as soon as it needs to be emptied. However, the system should also be able to detect and exclude false alarms - for example, when large objects such as pizza boxes block the fill level sensor, even though the garbage can still has space.

Goals

• Development of an intelligent waste garbage can with fill level sensors
• Integration of a system to avoid false alarms caused by large objects
• Connecting the garbage can to a network to transmit status information
• Development of a prototype that can be tested in a real environment
• Documentation of the work, presentation of the results on site

Requirements

• An independent and structured way of working
• Knowledge of a programming language
• Experience with LoRaWAN and the connection of sensor networks would be desirable
• Interest in computer vision and object recognition technologies
• Willingness to work with local authorities and to travel regularly to Rastatt