EcoNavix
Sachin Kumar, Anitej Suklikar, Samarth Parekh, Roshni Kainthan · Team EcoVisionaries
Submitted to AI Policy Hackathon at Johns Hopkins University. Sprint projects are early-stage work by participants, not Apart Research publications.
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.
Reviews
A promising idea, addressing a growing need for sustainable logistics solutions by leveraging real-time data and AI-driven optimizations.
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
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 project
@misc{kumar2024econavix,
title = {{EcoNavix}},
author = {Sachin Kumar and Anitej Suklikar and Samarth Parekh and Roshni Kainthan},
year = {2024},
month = oct,
note = {Submitted to AI Policy Hackathon at Johns Hopkins University, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/econavix}},
url = {https://apartresearch.com/sprints/projects/econavix}
}More from AI Policy Hackathon at Johns Hopkins University
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