SIH26236/Agriculture, FoodTech & Rural Development

Al-Based Intelligent Food Packaging Material Recommendation System for Food Commodities

Ministry of Food Processing Industries (MoFPI) · Software

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

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What they'll ask you

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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)

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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 SIH26236, set by Ministry of Food Processing Industries (MoFPI).
Its official title, word for word: "Al-Based Intelligent Food Packaging Material Recommendation System for Food Commodities"
Theme: Agriculture, FoodTech & Rural Development. Category: software.

## The organisers' full description, verbatim

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

<p>

Packaging plays a very important role in maintaining the quality, safety, and shelf life of food products during storage, transportation, and distribution. Different food commodities require different packaging materials depending on their physical, chemical, and biological properties.

</p>

<p>

Selection of improper packaging material may result in moisture absorption, oxidation, microbial spoilage, texture degradation, nutrient loss, and reduced shelf life. At present, packaging material selection is mostly dependent on expert knowledge and manual analysis. Small food industries, startups, farmers, and local manufacturers often face difficulties in selecting suitable packaging materials because of the lack of technical knowledge regarding barrier properties, permeability, storage conditions, and food-packaging compatibility.

</p>

<p>

Fresh fruits and vegetables also continue respiration after harvesting, which further complicates packaging selection because oxygen and carbon dioxide transmission through packaging films must be properly controlled. Therefore, there is a need for an intelligent software system that can automatically recommend optimized packaging materials and packaging specifications according to the properties of food commodities and storage requirements.

</p>

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

<p>

The proposed project aims to develop an AI-powered intelligent packaging recommendation application that suggests suitable packaging materials and packaging specifications for different food commodities. The system will take input parameters such as commodity type, moisture content, oil/fat content, pH, respiration rate, desired shelf life, storage temperature, relative humidity, transportation conditions, and storage type (ambient, chilled, or frozen).

</p>

<p>

Based on these parameters, the system will analyze the food properties using an AI-based recommendation engine and a packaging material database. The software will recommend suitable packaging materials such as LDPE, HDPE, PET, metalized films, aluminum foil laminates, biodegradable films, or breathable films depending on the product requirements.

</p>

<p>The application will also recommend important packaging specifications including:</p>

<ul>

<li>Oxygen Transmission Rate (OTR)</li>

<li>Water Vapor Transmission Rate (WVTR)</li>

<li>Film thickness</li>

<li>Sealability</li>

<li>Gas permeability</li>

<li>Mechanical strength</li>

<li>Modified Atmosphere Packaging (MAP) suitability</li>

</ul>

<p>

For fresh produce, the system will also consider respiration rate and suggest breathable or micro-perforated packaging materials along with recommended gas composition for MAP packaging.

</p>

<p>

The proposed solution may further include shelf-life prediction, sustainability analysis, cost optimization, QR-based traceability, and eco-friendly packaging recommendations. The system can be developed as a web application or mobile application using technologies such as Python, Flutter, Machine Learning, and database systems.

</p>

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

<p>

The expected solution is an intelligent software platform capable of automatically recommending optimized food packaging materials and packaging specifications for different commodities.

</p>

<p>The system should:</p>

<ul>

<li>Provide packaging recommendations based on food properties and environmental conditions.</li>

<li>Predict suitable barrier and permeability requirements.</li>

<li>Suggest packaging structures and thickness.</li>

<li>Recommend sustainable and recyclable alternatives.</li>

<li>Assist industries, farmers, startups, and researchers in selecting proper packaging solutions.</li>

<li>Improve shelf life, reduce food wastage, and minimize packaging-related losses.</li>

</ul>

<p>

The developed application should function as a smart decision-support tool for the food processing and packaging industry.

</p>

-->

Background:

Packaging plays a very important role in maintaining the quality, safety, and shelf life of food products during storage, transportation, and distribution. Different food commodities require different packaging materials depending on their physical, chemical, and biological properties.

Selection of improper packaging material may result in moisture absorption, oxidation, microbial spoilage, texture degradation, nutrient loss, and reduced shelf life. At present, packaging material selection is mostly dependent on expert knowledge and manual analysis. Small food industries, startups, farmers, and local manufacturers often face difficulties in selecting suitable packaging materials because of the lack of technical knowledge regarding barrier properties, permeability, storage conditions, and food-packaging compatibility.

Fresh fruits and vegetables also continue respiration after harvesting, which further complicates packaging selection because oxygen and carbon dioxide transmission through packaging films must be properly controlled. Therefore, there is a need for an intelligent software system that can automatically recommend optimized packaging materials and packaging specifications according to the properties of food commodities and storage requirements.

Description:

The proposed project aims to develop an AI-powered intelligent packaging recommendation application that suggests suitable packaging materials and packaging specifications for different food commodities. The system will take input parameters such as commodity type, moisture content, oil/fat content, pH, respiration rate, desired shelf life, storage temperature, relative humidity, transportation conditions, and storage type (ambient, chilled, or frozen).

Based on these parameters, the system will analyze the food properties using an AI-based recommendation engine and a packaging material database. The software will recommend suitable packaging materials such as LDPE, HDPE, PET, metalized films, aluminum foil laminates, biodegradable films, or breathable films depending on the product requirements.

The application will also recommend important packaging specifications including:

Oxygen Transmission Rate (OTR)

Water Vapor Transmission Rate (WVTR)

Film thickness

Sealability

Gas permeability

Mechanical strength

Modified Atmosphere Packaging (MAP) suitability

For fresh produce, the system will also consider respiration rate and suggest breathable or micro-perforated packaging materials along with recommended gas composition for MAP packaging.

The proposed solution may further include shelf-life prediction, sustainability analysis, cost optimization, QR-based traceability, and eco-friendly packaging recommendations. The system can be developed as a web application or mobile application using technologies such as Python, Flutter, Machine Learning, and database systems.

Expected Solution:

The expected solution is an intelligent software platform capable of automatically recommending optimized food packaging materials and packaging specifications for different commodities.

The system should:

Provide packaging recommendations based on food properties and environmental conditions.

Predict suitable barrier and permeability requirements.

Suggest packaging structures and thickness.

Recommend sustainable and recyclable alternatives.

Assist industries, farmers, startups, and researchers in selecting proper packaging solutions.

Improve shelf life, reduce food wastage, and minimize packaging-related losses.

The developed application should function as a smart decision-support tool for the food processing and packaging industry.
## 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.

## 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 (933 words)

Background: Packaging plays a very important role in maintaining the quality, safety, and shelf life of food products during storage, transportation, and distribution. Different food commodities require different packaging materials depending on their physical, chemical, and biological properties. Selection of improper packaging material may result in moisture absorption, oxidation, microbial spoilage, texture degradation, nutrient loss, and reduced shelf life. At present, packaging material selection is mostly dependent on expert knowledge and manual analysis. Small food industries, startups, farmers, and local manufacturers often face difficulties in selecting suitable packaging materials because of the lack of technical knowledge regarding barrier properties, permeability, storage conditions, and food-packaging compatibility. Fresh fruits and vegetables also continue respiration after harvesting, which further complicates packaging selection because oxygen and carbon dioxide transmission through packaging films must be properly controlled. Therefore, there is a need for an intelligent software system that can automatically recommend optimized packaging materials and packaging specifications according to the properties of food commodities and storage requirements. Description: The proposed project aims to develop an AI-powered intelligent packaging recommendation application that suggests suitable packaging materials and packaging specifications for different food commodities. The system will take input parameters such as commodity type, moisture content, oil/fat content, pH, respiration rate, desired shelf life, storage temperature, relative humidity, transportation conditions, and storage type (ambient, chilled, or frozen). Based on these parameters, the system will analyze the food properties using an AI-based recommendation engine and a packaging material database. The software will recommend suitable packaging materials such as LDPE, HDPE, PET, metalized films, aluminum foil laminates, biodegradable films, or breathable films depending on the product requirements. The application will also recommend important packaging specifications including: <ul> <li>Oxygen Transmission Rate (OTR)</li> <li>Water Vapor Transmission Rate (WVTR)</li> <li>Film thickness</li> <li>Sealability</li> <li>Gas permeability</li> <li>Mechanical strength</li> <li>Modified Atmosphere Packaging (MAP) suitability</li> </ul> For fresh produce, the system will also consider respiration rate and suggest breathable or micro-perforated packaging materials along with recommended gas composition for MAP packaging. The proposed solution may further include shelf-life prediction, sustainability analysis, cost optimization, QR-based traceability, and eco-friendly packaging recommendations. The system can be developed as a web application or mobile application using technologies such as Python, Flutter, Machine Learning, and database systems. Expected Solution: The expected solution is an intelligent software platform capable of automatically recommending optimized food packaging materials and packaging specifications for different commodities. The system should: <ul> <li>Provide packaging recommendations based on food properties and environmental conditions.</li> <li>Predict suitable barrier and permeability requirements.</li> <li>Suggest packaging structures and thickness.</li> <li>Recommend sustainable and recyclable alternatives.</li> <li>Assist industries, farmers, startups, and researchers in selecting proper packaging solutions.</li> <li>Improve shelf life, reduce food wastage, and minimize packaging-related losses.</li> </ul> The developed application should function as a smart decision-support tool for the food processing and packaging industry. --> Background: Packaging plays a very important role in maintaining the quality, safety, and shelf life of food products during storage, transportation, and distribution. Different food commodities require different packaging materials depending on their physical, chemical, and biological properties. Selection of improper packaging material may result in moisture absorption, oxidation, microbial spoilage, texture degradation, nutrient loss, and reduced shelf life. At present, packaging material selection is mostly dependent on expert knowledge and manual analysis. Small food industries, startups, farmers, and local manufacturers often face difficulties in selecting suitable packaging materials because of the lack of technical knowledge regarding barrier properties, permeability, storage conditions, and food-packaging compatibility. Fresh fruits and vegetables also continue respiration after harvesting, which further complicates packaging selection because oxygen and carbon dioxide transmission through packaging films must be properly controlled. Therefore, there is a need for an intelligent software system that can automatically recommend optimized packaging materials and packaging specifications according to the properties of food commodities and storage requirements. Description: The proposed project aims to develop an AI-powered intelligent packaging recommendation application that suggests suitable packaging materials and packaging specifications for different food commodities. The system will take input parameters such as commodity type, moisture content, oil/fat content, pH, respiration rate, desired shelf life, storage temperature, relative humidity, transportation conditions, and storage type (ambient, chilled, or frozen). Based on these parameters, the system will analyze the food properties using an AI-based recommendation engine and a packaging material database. The software will recommend suitable packaging materials such as LDPE, HDPE, PET, metalized films, aluminum foil laminates, biodegradable films, or breathable films depending on the product requirements. The application will also recommend important packaging specifications including: Oxygen Transmission Rate (OTR) Water Vapor Transmission Rate (WVTR) Film thickness Sealability Gas permeability Mechanical strength Modified Atmosphere Packaging (MAP) suitability For fresh produce, the system will also consider respiration rate and suggest breathable or micro-perforated packaging materials along with recommended gas composition for MAP packaging. The proposed solution may further include shelf-life prediction, sustainability analysis, cost optimization, QR-based traceability, and eco-friendly packaging recommendations. The system can be developed as a web application or mobile application using technologies such as Python, Flutter, Machine Learning, and database systems. Expected Solution: The expected solution is an intelligent software platform capable of automatically recommending optimized food packaging materials and packaging specifications for different commodities. The system should: Provide packaging recommendations based on food properties and environmental conditions. Predict suitable barrier and permeability requirements. Suggest packaging structures and thickness. Recommend sustainable and recyclable alternatives. Assist industries, farmers, startups, and researchers in selecting proper packaging solutions. Improve shelf life, reduce food wastage, and minimize packaging-related losses. The developed application should function as a smart decision-support tool for the food processing and packaging industry.