Objectives.

This project focused on developing a sustainable mobile app using the Ionic framework. The initial phase prioritised the integration of a “Travel Dashboard” and advanced AI for “Travel Mode Detection.

  • Promoting Sustainability: Encouraging eco-friendly actions and monitoring carbon emissions.
  • Ensuring Regulatory Compliance: Facilitating seamless climate-related reporting for businesses.
  • Enhancing User Engagement: Active user involvement in sustainability efforts with insightful features.
  • AI Integration: Enhancing accuracy and user experience with advanced AI technology.
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Our Solutions.

To achieve the objectives, Systango developed an AI-based system. This solution seamlessly integrated the “Travel Dashboard” and implemented AI-powered “Travel Mode Detection,” while also incorporating emission calculations into the app’s dashboard for valuable environmental insights. The solution includes:

  • Data Collection and Preprocessing

    Ensured accuracy and reliability of raw mobile device data.

  • Feature Engineering

    Transformed data into meaningful features for precise transport mode prediction.

  • Model Selection and Training

    Utilised rigorous training of machine learning models like Logistic Regression, Random Forest, and KNN.

  • Accuracy Validation and Integration

    Implemented the effectiveness of the AI model through validation processes and integrated geofencing for accurate travel mode detection.

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Key Benefits.

  • Reduced carbon emissions by 30%
  • Increased eco-friendly user actions
  • Streamlined regulatory compliance processes
  • Enhanced user engagement with insights
  • Improved accuracy in travel detection
  • Comprehensive environmental impact tracking

Tech Stack.

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