Vision AI

The problem starts when customer puts the wrong waste that does not belong there such as plastic waste in a food waste bin which leads to Contamination.
Contamination generates financial costs for the hauler and processor and environmental costs in that potentially valuable resources are diverted to landfill.
To combat this, haulers require a smarter and automated solution that can identify contamination at the point of collection and provide the necessary evidence of contamination to support customer education.

For efficient solution, we started with implementing the agile startegy. This method of working is the greatest and it helps in making the process more flexible because Iteration is the key to best design.

I always begin a project by including users as soon as feasible and start building user personas to deep dive into the project. And the major personas we consider were - the waste industry specialists, truck drivers, the COO (chief operating officer), depot managers.

It was a whole new concept and in order to design the best experience, I collected every information from Product Owner and Manager. I went to see how the process actually works inside the system.

Built up the rough structure, paper wireframing, discussed with my team for all the posibilities. It was important to conveniently arrange the elements on the screens and provide an intuitive structure of the application.

Featured in April 2022 issue of Waste Advantage Magazine. Artificial Intelligence and Machine Learning are here to stay. They are already making a difference for recycling and waste management companies in the areas of automating a process to reduce cost, improve productivity, and/or increasing safety.