SIH26233/Agriculture, FoodTech & Rural Development

Inline Microbial Contamination Detection Using Hyperspectral

Ministry of Food Processing Industries (MoFPI) · Hardware

Teams already in: Not read yet
Buildable in 36 hours: Not decoded
Hard blockers: NoneNothing you must source first
Submissions close: 15 Sept9 days left

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Submit on sih.gov.in

Whether this suits your team

Not decoded yet

We have this problem statement but have not run it through our decode pass. The government’s own description is below, unchanged.

What they'll ask you

Generated from the brief's own wording and the competition's published rules — never from a guess about what this ministry prefers.

We have not run our decode pass over this one yet, so these are the questions asked of every team rather than questions about this problem statement. The organisers’ own description is on this page, unchanged.

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.
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.

1 more— the ones a panel gets to if there is time

Which single thing will you demonstrate end to end, start to finish, with nothing skipped?

The data

What the organisers attached, and what the brief assumes you can get.

Dataset from the organisers: None attached
Does the brief need data?: Nothing in the text says it depends on a dataset we would have to find.

Also from Ministry of Food Processing Industries (MoFPI)

Same organisation, same year. Reading two of theirs tells you more about what they care about than reading one.

Take this to an AI

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.

# Context: India's Smart India Hackathon 2026

I am on a student team entering SIH 2026. Problem statement SIH26233, set by Ministry of Food Processing Industries (MoFPI).
Its official title, word for word: "Inline Microbial Contamination Detection Using Hyperspectral"
Theme: Agriculture, FoodTech & Rural Development. Category: hardware.

## The organisers' full description, verbatim

<p><strong>Background:</strong></p>

<p>

Food safety practices are largely reactive. Plants typically pull random samples from production batches and send them to laboratories for culture testing. Because these tests take days to yield results, contaminated products are often already packaged and shipped by the time pathogens are detected. This delay triggers widespread, costly product recalls and severe public health risks.

</p>

<p><strong>Description:</strong></p>

<p>

The sector requires an inline, non-destructive hardware sensing system that scans 100% of products moving along a production line. The hardware must detect invisible bacterial biofilms and early-stage pathogens, such as Salmonella, Listeria, or E. coli, directly on food surfaces, such as fresh poultry or leafy greens, without stopping or destroying the product.

</p>

<p><strong>Expected Solution:</strong></p>

<p>

An inline Hyperspectral Imaging (HSI) sensor rig positioned directly over industrial conveyor systems. The hardware must utilize specialized Near-Infrared (NIR) or ultraviolet light sources to capture distinct spectral signatures of microbial contamination.

</p>

<p>

It must feature high-speed edge-computing processors built directly into the sensor housing to flag contaminated items within milliseconds, instantly alerting downstream sorting mechanisms to isolate the hazard.

</p>

-->

Background:

Food safety practices are largely reactive. Plants typically pull random samples from production batches and send them to laboratories for culture testing. Because these tests take days to yield results, contaminated products are often already packaged and shipped by the time pathogens are detected. This delay triggers widespread, costly product recalls and severe public health risks.

Description:

The sector requires an inline, non-destructive hardware sensing system that scans 100% of products moving along a production line. The hardware must detect invisible bacterial biofilms and early-stage pathogens, such as Salmonella, Listeria, or E. coli, directly on food surfaces, such as fresh poultry or leafy greens, without stopping or destroying the product.

Expected Solution:

An inline Hyperspectral Imaging (HSI) sensor rig positioned directly over industrial conveyor systems. The hardware must utilize specialized Near-Infrared (NIR) or ultraviolet light sources to capture distinct spectral signatures of microbial contamination.

It must feature high-speed edge-computing processors built directly into the sensor housing to flag contaminated items within milliseconds, instantly alerting downstream sorting mechanisms to isolate the hazard.
## Constraints that are not negotiable

- The judged build is a prototype demonstrated in roughly 36 hours by students, not a product.
- A jury evaluates it against this problem statement's own wording, not against general merit.
- We submit on sih.gov.in; the problem statement number and title above must match exactly.
- Your solution must not have appeared in any previous event or programme, of any sort.
- This is a hardware problem statement, so a demo needs physical components we source ourselves.

## What I want from you

1. Who actually has this problem in India, and what they do about it today.
2. What already exists — government systems, open-source projects, published research — that we should not rebuild.
3. For each item under 'what the brief never says', what the realistic answer is likely to be and how I could verify it.
4. The two or three things about this domain that a student team would get wrong without local knowledge.
## How to answer

- Everything above between quotation marks is the organisers' own wording. Treat it as the requirement.
- Do NOT invent requirements the brief does not state. If something matters and is not stated, say so and ask me, rather than assuming.
- Where you are inferring rather than reading, mark it as your inference.
- Do not guess what this ministry wants from its name. Its wording above is the only evidence.

---
Problem statement facts assembled by Wynit from Ministry of Food Processing Industries (MoFPI)'s published brief for SIH 2026.
The plain-English summary, the list of parts and the evaluator read are our interpretation of that text; the quoted title and the full description are theirs.

The government's original description (353 words)

Background: Food safety practices are largely reactive. Plants typically pull random samples from production batches and send them to laboratories for culture testing. Because these tests take days to yield results, contaminated products are often already packaged and shipped by the time pathogens are detected. This delay triggers widespread, costly product recalls and severe public health risks. Description: The sector requires an inline, non-destructive hardware sensing system that scans 100% of products moving along a production line. The hardware must detect invisible bacterial biofilms and early-stage pathogens, such as Salmonella, Listeria, or E. coli, directly on food surfaces, such as fresh poultry or leafy greens, without stopping or destroying the product. Expected Solution: An inline Hyperspectral Imaging (HSI) sensor rig positioned directly over industrial conveyor systems. The hardware must utilize specialized Near-Infrared (NIR) or ultraviolet light sources to capture distinct spectral signatures of microbial contamination. It must feature high-speed edge-computing processors built directly into the sensor housing to flag contaminated items within milliseconds, instantly alerting downstream sorting mechanisms to isolate the hazard. --> Background: Food safety practices are largely reactive. Plants typically pull random samples from production batches and send them to laboratories for culture testing. Because these tests take days to yield results, contaminated products are often already packaged and shipped by the time pathogens are detected. This delay triggers widespread, costly product recalls and severe public health risks. Description: The sector requires an inline, non-destructive hardware sensing system that scans 100% of products moving along a production line. The hardware must detect invisible bacterial biofilms and early-stage pathogens, such as Salmonella, Listeria, or E. coli, directly on food surfaces, such as fresh poultry or leafy greens, without stopping or destroying the product. Expected Solution: An inline Hyperspectral Imaging (HSI) sensor rig positioned directly over industrial conveyor systems. The hardware must utilize specialized Near-Infrared (NIR) or ultraviolet light sources to capture distinct spectral signatures of microbial contamination. It must feature high-speed edge-computing processors built directly into the sensor housing to flag contaminated items within milliseconds, instantly alerting downstream sorting mechanisms to isolate the hazard.