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Takeaway services are now essential to the functioning of our cities, but delivery riders face low pay, job insecurity, and hazardous working conditions. Food-delivery platforms prioritise efficiency over riders' well-being, resulting in a substantial power and information imbalance, which create the conditions for further exploitation. Taking a rider’s perspective, this project explores the emotive experience of takeaway riders on the streets of London via machine learning-driven video and image analysis. The team worked further on two separate design proposals.
The Dignity Project proposes an ethical navigational platform that replaces the shorter path algorithm used by the ubiquitous Google Maps with an emotional health algorithm, driving the riders through the ‘happier route’ to the destination. The proposed navigation platform is further expanded by a dynamic network of shelters that provide resting and communal areas for the drivers.
App-based support for delivery drivers by providing optimised routes and a flexible shelter system.
Delivery riders use recording devices such as wearable cameras while delivering food to capture the whole process from their point of view.
The analysis of video recordings reveals the challenges and needs of delivery drivers.
The algorithm determines routes based on higher sentiment scores, safety data, and improved support infrastructure, including supermarkets, parks and restrooms.
Each route is assigned a happiness score for delivery drivers, which helps guide the placement of additional shelters and rest areas.
The shelters offer temporary spaces for resting and cooking, while the inflatable membrane enables multiple units to be connected around a shared communal area.