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Objective: To create an IoT-driven solution for real-time restroom cleanliness assessment through odour detection and integrated machine learning for air quality analysis.
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Technologies Used: Python, Django, Rest APIs, Bootstrap.
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Description: This project aimed to revolutionize restroom hygiene by developing a system that assessed cleanliness in real-time through odour detection and used machine learning for air quality analysis. The technologies employed included Python for scripting, Django for web development, Rest APIs for data communication, and Bootstrap for frontend design.
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Key Achievements:
- Implemented IoT sensors for odour detection.
- Integrated machine learning algorithms for air quality analysis.
- Developed a user-friendly web interface for real-time monitoring.
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Duration: 3 Months
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Team Size: 3
