Bharat Electronics Limited
Browse and strategize across all 5 official problem statements submitted by Bharat Electronics Limited for Smart India Hackathon 2026.
Problem Statements (5)
Match My TeamEdge-AI Based Distributed Fleet Coordination for Autonomous Mobile Robots (AMRs) in Smart Warehouses
Autonomous Mobile Robots (AMRs) operating in dynamic industrial warehouses and military logistics depots suffer from collision deadlocks and network latency bottlenecks when coordinated by centralized servers. Build an Edge-AI Based Distributed Fleet Coordination and Decentralized Multi-Agent Path Finding (MAPF) platform for Bharat Electronics Limited (BEL) that uses peer-to-peer V2X communication, spatial reservation grids, and distributed consensus to coordinate 50+ AMRs in GPS-denied environments with zero central point of failure.
AI-Powered Mobile Urban Intelligence Platform Using Public Transport Fleet
Smart city surveillance and road infrastructure monitoring across Indian municipal corporations is hindered by the high cost of installing fixed road cameras every 100 meters. Build an AI-Powered Mobile Urban Intelligence Platform for Bharat Electronics Limited (BEL) that mounts edge-AI camera units on public city buses to continuously detect road potholes, illegal roadside encroachment, garbage overflow, and missing streetlights during daily transit routes.
Blockchain-Based Secure Platform for Identity,Access Control, and Digital Asset Management
Defense establishments and critical public sector enterprises under Bharat Electronics Limited (BEL) face severe insider threats, credential theft, and unauthorized facility access due to fragmented identity silos and centralized database vulnerabilities. Build a Blockchain-Based Self-Sovereign Identity (SSI), Zero-Trust Access Control, and Digital Credential Platform for BEL that uses Decentralized Identifiers (DIDs), Verifiable Credentials (W3C standard), and post-quantum cryptographic signatures to secure multi-facility biometric access.
Vision Based Autonomous Navigation for Unmanned Ground Vehicle for Outdoor environment
Unmanned Ground Vehicles (UGVs) deployed in military border reconnaissance and tactical off-road missions face severe GPS-denial, electronic jamming, and unpredictable rough terrain (boulders, ditches, tall grass) where standard wheel-odometry fails due to tire slip. Build a Vision-Based Autonomous Navigation and Visual-Inertial SLAM System for UGVs for Bharat Electronics Limited (BEL) combining stereo visual odometry, semantic terrain traversability estimation, and dynamic obstacle avoidance in GPS-denied tactical environments.
City-Wide AI Engine for Multi-Camera ANPR Trajectory Tracking and Urban Traffic Analytics
Police and traffic authorities across major Indian cities struggle to track stolen suspect vehicles or reckless drivers across thousands of disconnected municipal CCTV cameras because manual camera switching is slow and vehicles change appearance across different lighting angles. Build a City-Wide AI Engine for Multi-Camera ANPR Trajectory Tracking and Urban Mobility for Bharat Electronics Limited (BEL) that automatically extracts vehicle license plates, computes spatial-temporal re-identification (ReID) embeddings, and reconstructs 2D/3D vehicle travel routes on a city GIS map in real time.