EcoNavix

Sachin Kumar, Anitej Suklikar, Samarth Parekh, Roshni Kainthan

EcoNavix is an AI-powered, eco-conscious route optimization platform designed to help logistics companies reduce carbon emissions while maintaining operational efficiency. By integrating real-time traffic, weather, and emissions data, EcoNavix provides optimized routes that minimize environmental impact and offers actionable insights for sustainable decision-making in supply chain operations.

Reviewer's Comments

Reviewer's Comments

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Yu Fan

A promising idea, addressing a growing need for sustainable logistics solutions by leveraging real-time data and AI-driven optimizations.

Kevin Xu

Pretty good idea, I saw in the code base for route optimization it was a constant multiple of the original values, which is fine for a hackathon but alternativelty could've probably tried two different APIs, and then make the better one the "optimized" one so there's actually 2 different routes. Also the vercel site doesn't work, but I'm assuming that's because of the flask backend instead of leveraging vercel's next infra to put everything together so benefit of the doubt that the backend would work

Axel Backlund

Relevant and important problem adressed, well presented and impressed with the technical readiness. A more detailed explanation on how the optimized route is calculated would however be beneficial, as it seems that the core contribution is regarding this. It is understandable that the time constraint did not allow for a finished products, but some ideas on how this can be achieved would have ben great.

Cite this work

@misc {

title={

@misc {

},

author={

Sachin Kumar, Anitej Suklikar, Samarth Parekh, Roshni Kainthan

},

date={

10/27/24

},

organization={Apart Research},

note={Research submission to the research sprint hosted by Apart.},

howpublished={https://apartresearch.com}

}

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This work was done during one weekend by research workshop participants and does not represent the work of Apart Research.
This work was done during one weekend by research workshop participants and does not represent the work of Apart Research.