Week #1 #

Project description #

Project name: Kolobok #

Code repository: https://github.com/IU-Capstone-Project-2025/Kolobok

Many car service centers offer tire trade-ins, but pricing used tires is slow and error-prone. It typically requires manual measurement of tread depth and a subjective evaluation of spike wear, which is not scalable.

This project uses machine learning to automate tire valuation. Users send two photos of a tire to a Telegram bot. The system then detects the brand and parameters, estimates tread depth, and analyzes the condition of spikes.

The solution is designed for both car owners and retail employees, reducing manual workload and enabling remote consultations. Developed in response to a real-world need from a mid-sized car services.

Team Members #

Brainstorming #

Ideas during brainstorming #

1. Tire Valuation System (Chosen):
   ML-powered analysis of tire condition through photos
2. Virtual Car Detailing Platform:
   App for visualizing car modifications + service pricing
3. Automated Maintenance Tracker:
   Service scheduling platform + maintenance history

Brief market research / problem validation (1st idea) #

• No comprehensive solutions combining brand detection, tread measurement and spike analysis
• One brand detection solution using CV was found, however, we have a better idea (need testing)
• 2 car services will be pilot platform for our solution

Basic requirements #

Target users and their primary needs #

1. Car owners:
   Quickly value tires for sale/trade-in without visiting service center
2. Retail employees:
   Accelerate tire evaluation process during customer interactions
3. Service managers:
   Maintain consistent pricing routines across car service centers

User stories #

1. As a car owner, I want to photograph my tires and get instant valuation of thread depth and spikes condition so I can sell them faster
2. As retail staff, I want automated tread measurements and spikes analysis to reduce human error in evaluations
3. As a service manager, I want remote tire valuation to scale operations and accelerate processes

Initial scope #

Tech-stack #

Additional notes #

• Kanban board created for task tracking
• Initial research on tire measurement algorithms completed
• Team communication channels established (Telegram)

Weekly commitments #

Individual contribution of each participant #

Confirmation of the code’s operability #

We confirm that the code in the main branch:

• In working condition
• Run via method described in README.md