End-to-End transportation mode recognition software
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About
Codos platform motivates people all around the world to shift their commuting patterns away from regular combustion engine cars, towards environmentally friendly modes of commuting. The Codos App uses machine learning and AI to automatically detect the form of transport you are using in a privacy-preserving way, in order to measure the avoidance of CO2 compared to using a car. Read more
CASE STUDY DETAILS
Codos Foundation
Seed to Series A Startup
., Switzerland
Project work
6 - 10 people
6 - 9 Months
€250 - 1M
Scrum
FOCUS AREA
Challenge, approach, and impact
The challenge
Reasonfield Lab by SoftwareMill was to create an end-to-end solution for the Codos Foundation, which involved detecting transportation modes based on data from mobile phones. The goal was to calculate CO2 emission avoidance to reward users for sustainable commuting. The project required high precision in machine learning models and handling continuous mobile sensor data. Understanding the spatial context was crucial since user motion occurs in cities, making the task a challenging combination of science and engineering.
Testimonials
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Anonymous
CEO at Codos Foundation
VERIFIED
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Anonymous
CEO at Codos Foundation
VERIFIED
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Anonymous
CEO at Codos Foundation
VERIFIED
“...“ Read more
Anonymous
CEO at Codos Foundation
VERIFIED
“...“ Read more
Anonymous
CEO at Codos Foundation
VERIFIED
“...“ Read more
Anonymous
CEO at Codos Foundation
VERIFIED
Team Structure
Client Team
Daily point of contact
CEO
***** *****
The client stakeholders at Codos Foundation were working closely with the team at SoftwareMill
Agency Team
Production
1 x Architect