A retail intelligence platform that uses on-device AI and smart cameras to monitor shopper traffic, track inventory, and manage checkout queues.
Qualcomm Inc · Hardware
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Decomposed from what the description asks for. Nothing added.
Shopper Analytics Module
Detects customer counts, footfall trends, dwell times, and movement heatmaps using video streams.
Inventory Monitoring Module
Detects stock shortages, checks product placement against plans, and alerts staff for replenishment.
Queue Intelligence Module
Monitors checkout lines, predicts congestion, and recommends opening extra counters based on wait times.
Edge AI Processing Engine
Runs computer vision models locally on edge hardware to maintain operation during internet disruptions.
Privacy and Security Layer
Processes data locally and uses anonymous tracking to avoid storing personally identifiable information.
Store Operations Dashboard
Displays real-time alerts, daily and weekly reports, and KPI visualizations for store staff.
Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.
The evaluators will check whether the AI models run locally on edge hardware without constant cloud access, if customer privacy is maintained through anonymous tracking, and if the system delivers the requested analytics for footfall, inventory, and queues.
A jury can still ask about these. Decide them deliberately rather than by accident.
Generated from the brief's own wording and the competition's published rules — never from a guess about what this ministry prefers.
Specific edge hardware models or specifications to target?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Integration protocols or APIs for existing POS and ERP systems?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Target accuracy percentages for computer vision models?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Has any part of this been shown at a previous event, hackathon or college project?
The guidelines are explicit: your solution must not have appeared in any previous event or programme, of any sort. A recycled project is what a team under time pressure reaches for.
Each one is quoted from a gap in the brief, not a guess about your team.
Needs physical hardware
Listed as a hardware problem statement, so a working demo needs physical components you have to source yourself.
Needs data you may not get
The system requires video feeds from retail store cameras and integration with store POS, inventory management, and ERP systems which students typically cannot access.
What the organisers attached, and what the brief assumes you can get.
Same organisation, same year. Reading two of theirs tells you more about what they care about than reading one.
Pick what you are about to do and copy the prompt. It carries the organisers' own wording, the constraints they never spell out, and an instruction not to invent requirements they never set.
Who has this problem, what already exists, and what you would have to find out.
The brief asks for shopper analytics module. How would you build that?
Decoded from SIH26179 itself — Detects customer counts, footfall trends, dwell times, and movement heatmaps using video streams. The brief asks for it by name.
The brief asks for inventory monitoring module. How would you build that?
Decoded from SIH26179 itself — Detects stock shortages, checks product placement against plans, and alerts staff for replenishment. The brief asks for it by name.
The brief asks for queue intelligence module. How would you build that?
Decoded from SIH26179 itself — Monitors checkout lines, predicts congestion, and recommends opening extra counters based on wait times. The brief asks for it by name.
The brief asks for edge ai processing engine. How would you build that?
Decoded from SIH26179 itself — Runs computer vision models locally on edge hardware to maintain operation during internet disruptions. The brief asks for it by name.
The brief asks for privacy and security layer. How would you build that?
Decoded from SIH26179 itself — Processes data locally and uses anonymous tracking to avoid storing personally identifiable information. The brief asks for it by name.
The brief asks for store operations dashboard. How would you build that?
Decoded from SIH26179 itself — Displays real-time alerts, daily and weekly reports, and KPI visualizations for store staff. The brief asks for it by name.
Where does your data come from — a published source, one you collect, or one you generate?
No dataset is attached to this problem statement, so sourcing it is part of the work and nobody told you that.
Why not use what already exists? Name the closest thing to this that is already running.
A team that has not named the alternative themselves is answering this for the first time in the room.
Which single thing will you demonstrate end to end, start to finish, with nothing skipped?
Ours, not a rule: a narrow thing that fully works survives questioning better than a broad thing that half works. If nobody on the team can name it, that is the finding.
Show me this working: the evaluators will check whether the AI models run locally on edge hardware without constant cloud access, if customer privacy is maintained through anonymous tracking, and if the system delivers the requested analytics for footfall, inventory, and queues.
This is the evaluator read for your problem statement, decoded from the brief's own wording.