Enhancing AI Logistics & Disaster-Resilience Platform
Budget / Salary₹1,500–12,500
TypeFreelance project
LocationRemote
Posted1 hour ago
Project Title
NER-SMART: AI-Powered Logistics & Disaster-Resilience Platform for Northeast India (Streamlit)
Project Overview
NER-SMART is a Streamlit-based logistics intelligence platform built for the Northeast Indian Region (NER) — a hilly, disaster-prone corridor where landslides, flooding, and road closures routinely disrupt supply chains. The app models the region's road network as a live graph, blends weather + terrain + incident data through a machine-learning risk model, and gives field teams a single dashboard to plan routes, track vehicles, log incidents, and simulate disaster scenarios before they happen.
The core app is built and functional. I'm looking for a freelancer to help polish, debug, and extend it.
Key Features (already built)
GIS Map — interactive map of NER districts and highway network
AI Risk Prediction — a RandomForest model (scikit-learn) that scores road-segment risk from rainfall, slope, traffic, and incident history, with a transparent contribution breakdown
Route Optimizer — real road routing via OSRM, comparing AI-recommended / fastest / lowest-risk paths with live ETA and risk scoring
Fleet Tracking — live map of vehicles in transit, with GPS trail history and a documented JSON API contract for connecting real GPS hardware
Field Reports — geo-tagged incident reporting (landslide, flood, road damage, etc.) that instantly feeds back into the live risk model
Disaster Simulator — adjustable sliders (rainfall multiplier, landslide bias, road-condition penalty) to stress-test the network under hypothetical scenarios
AI Copilot — a rule-based natural-language Q&A interface over the live network state (road risk, blocked roads, safest routes, at-risk vehicles, open incidents)
Tech Stack
Python · Streamlit · scikit-learn · NetworkX · Folium / streamlit-folium · Pandas/NumPy · OSRM routing API · Streamlit Community Cloud
Scope of Work (customize as needed)
Fix outstanding bugs (map rendering, route calculation edge cases, layout issues)
Resolve deployment issues on Streamlit Community Cloud (Python version pinning, dependency conflicts)
Improve the AI Copilot with real LLM integration (Anthropic/OpenAI API) instead of the current rule-based fallback
Add authentication / multi-user support
Connect a real GPS/IoT data source to Fleet Tracking
General UI/UX polish and mobile responsiveness
Code review and refactor for production readiness
Ideal Candidate
Strong Python + Streamlit experience
Familiarity with geospatial tools (Folium, OSRM, or similar routing APIs)
Comfortable with scikit-learn / basic ML model integration
Bonus: experience with disaster-response or logistics-domain applications
Deliverables
Working, deployed Streamlit app (Community Cloud or platform of your choice)
Clean, commented, version-controlled code (GitHub)
Brief documentation of any changes made
Timeline & Budget
(fill in your specifics — e.g. "1–2 weeks, fixed price" or "ongoing, hourly")
NER-SMART: AI-Powered Logistics & Disaster-Resilience Platform for Northeast India (Streamlit)
Project Overview
NER-SMART is a Streamlit-based logistics intelligence platform built for the Northeast Indian Region (NER) — a hilly, disaster-prone corridor where landslides, flooding, and road closures routinely disrupt supply chains. The app models the region's road network as a live graph, blends weather + terrain + incident data through a machine-learning risk model, and gives field teams a single dashboard to plan routes, track vehicles, log incidents, and simulate disaster scenarios before they happen.
The core app is built and functional. I'm looking for a freelancer to help polish, debug, and extend it.
Key Features (already built)
GIS Map — interactive map of NER districts and highway network
AI Risk Prediction — a RandomForest model (scikit-learn) that scores road-segment risk from rainfall, slope, traffic, and incident history, with a transparent contribution breakdown
Route Optimizer — real road routing via OSRM, comparing AI-recommended / fastest / lowest-risk paths with live ETA and risk scoring
Fleet Tracking — live map of vehicles in transit, with GPS trail history and a documented JSON API contract for connecting real GPS hardware
Field Reports — geo-tagged incident reporting (landslide, flood, road damage, etc.) that instantly feeds back into the live risk model
Disaster Simulator — adjustable sliders (rainfall multiplier, landslide bias, road-condition penalty) to stress-test the network under hypothetical scenarios
AI Copilot — a rule-based natural-language Q&A interface over the live network state (road risk, blocked roads, safest routes, at-risk vehicles, open incidents)
Tech Stack
Python · Streamlit · scikit-learn · NetworkX · Folium / streamlit-folium · Pandas/NumPy · OSRM routing API · Streamlit Community Cloud
Scope of Work (customize as needed)
Fix outstanding bugs (map rendering, route calculation edge cases, layout issues)
Resolve deployment issues on Streamlit Community Cloud (Python version pinning, dependency conflicts)
Improve the AI Copilot with real LLM integration (Anthropic/OpenAI API) instead of the current rule-based fallback
Add authentication / multi-user support
Connect a real GPS/IoT data source to Fleet Tracking
General UI/UX polish and mobile responsiveness
Code review and refactor for production readiness
Ideal Candidate
Strong Python + Streamlit experience
Familiarity with geospatial tools (Folium, OSRM, or similar routing APIs)
Comfortable with scikit-learn / basic ML model integration
Bonus: experience with disaster-response or logistics-domain applications
Deliverables
Working, deployed Streamlit app (Community Cloud or platform of your choice)
Clean, commented, version-controlled code (GitHub)
Brief documentation of any changes made
Timeline & Budget
(fill in your specifics — e.g. "1–2 weeks, fixed price" or "ongoing, hourly")
Apply on Freelancer →
Project sourced from Freelancer.com. Applications happen directly on the original platform — we never collect your data.