SIH26025/Smart Automation

Mine subsidence early warning system

A web and mobile platform connected to low-cost wireless sensors that detects ground movement over underground coal mines and sends early warning alerts.

Ministry of Coal · Coal India Limited · Hardware

Teams already in: 2/500almost everyone who enters · read 1 hour ago
Buildable in 36 hours: LowOur estimate, from their wording
Hard blockers: 2Needs hardware, No dataset given
Submissions close: 15 Sept9 days left

Make this one of our two Compare with others

Signing in saves it for your whole team — everyone on your invite link sees the same two entries. Anything you shortlisted while signed out comes with you.

Submit on sih.gov.in

Whether this suits your team

Why this fits you

This organisation declared winners on 3 problem statement(s) in SIH 2025 and on 4 in SIH 2024. It has awarded 8 joint winner(s), so it sometimes splits a prize between two teams.

What argues against it

Potential concern: needs physical hardware.
Potential concern: no dataset provided.

What you would have to build

Decomposed from what the description asks for. Nothing added.

01
Sensor Node Hardware
Build low-cost smart sensor nodes using readily available hardware like Arduino, ESP32, or Raspberry Pi.
02
Wireless Mesh Network
Connect sensor nodes using a wireless mesh communication network such as LoRa, Zigbee, or Wi-Fi mesh.
03
AI Anomaly Detection
Implement machine learning models to identify abnormal deformation patterns and predict subsidence zones.
04
GIS Dashboard
Create an interactive web or mobile dashboard with GIS visualization for live deformation maps and risk zones.
05
Early Warning Alerts
Configure an automated notification system that sends alerts through SMS, email, or app notifications.

What they ask for, and what they leave open

Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.

They state

The jury will check if your prototype uses low-cost hardware like ESP32 or Arduino, demonstrates wireless mesh communication between nodes, uses AI for anomaly detection, and includes a GIS-based dashboard with automated alerts.

They never say

exact historical subsidence datasets for model training
specific thresholds for tilt, vibration, and displacement that constitute an emergency

A jury can still ask about these. Decide them deliberately rather than by accident.

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.

Exact historical subsidence datasets for model training?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Specific thresholds for tilt, vibration, and displacement that constitute an emergency?
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.

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

The brief asks for sensor node hardware. How would you build that?
Decoded from SIH26025 itself — Build low-cost smart sensor nodes using readily available hardware like Arduino, ESP32, or Raspberry Pi. The brief asks for it by name.

Before you commit

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.
No dataset provided
The description depends on real data, and the organisers have not attached a dataset link.

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?: Yes, and none is attached — finding or generating it is part of the work.

Also from Ministry of Coal

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 SIH26025, set by Ministry of Coal.
Its official title, word for word: "Development of an AI-enabled Low Cost Real Time Mine Subsidence Monitoring, Prediction and Early Warning System for Underground Coal Mines in India"
Theme: Smart Automation. Category: hardware.

In plain terms: A web and mobile platform connected to low-cost wireless sensors that detects ground movement over underground coal mines and sends early warning alerts.

## The organisers' full description, verbatim

Background: Surface subsidence caused by underground coal mining poses significant risks to nearby communities, public infrastructure, agricultural land, forest areas, and the surrounding environment. In India, subsidence monitoring is still largely dependent on conventional field observations, periodic surveys, and post facto damage assessments, which often fail to provide timely warning before critical ground failure occurs. There is a strong need for an indigenous, low cost, intelligent, and real time monitoring solution capable of detecting early signs of ground movement and enabling proactive risk mitigation. Such a system should be affordable, scalable, and deployable across Indian underground coal mines using widely accessible technologies, thereby supporting the national vision of smart and sustainable mining. Description: The problem envisages development of an AI-enabled smart mine subsidence monitoring and early warning platform based on a localized wireless surface mesh sensor network deployed above underground mine panels. The proposed solution involves installing a distributed network of low cost smart sensor nodes across the surface over the underground mining area. Each node may be equipped with sensors such as: • tilt/inclination sensors, • vibration sensors, • displacement/stretch sensors, • crack detection sensors, • optional low cost positioning modules. These nodes will communicate through a wireless mesh communication network (such as LoRa/Zigbee/Wi-Fi mesh), enabling continuous real time monitoring of micro ground movements over the mine panel. The system should continuously detect: • abnormal ground tilt, • change in relative distance between nodes, • early crack initiation, • unusual vibration signatures, which may indicate the onset of subsidence. Using Artificial Intelligence / Machine Learning, the platform should: • identify abnormal deformation patterns, • predict possible subsidence zones, • estimate severity and progression, • generate automated early warning alerts, • support timely operational decisions. The solution should be robust, low power, scalable, and suitable for Indian geo-mining conditions. Expected Solution: A web/mobile enabled intelligent mine subsidence monitoring platform integrating IoT, wireless mesh networking, AI, and GIS technologies for: • development of low cost smart sensor nodes using readily available hardware platforms (e.g., Arduino/ESP32/Raspberry Pi); • deployment of a localized wireless mesh network over underground mine panels for continuous surface deformation sensing; • real time monitoring of tilt, displacement, vibration, and crack initiation; • AI/ML-based anomaly detection and subsidence prediction using live and historical data; • GIS based visualization of live deformation maps and risk zones; • automated early warning alerts through SMS/email/mobile app notifications; • interactive dashboards for mine operators, planners, and regulators; • offline capability with periodic cloud synchronization; • scalable deployment across multiple underground coalfields. The proposed solution must be low cost, easy to deploy, energy efficient, scalable, and student prototype friendly, while enabling a Made in India smart mining safety solution for sustainable underground coal mining. Now your problem statement has a clear unique innovation hook: 'Wireless Surface Mesh Network for Real Time Subsidence Detection' that is what will differentiate it from generic AI proposals.

## What the brief never says

- exact historical subsidence datasets for model training
- specific thresholds for tilt, vibration, and displacement that constitute an emergency
## 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.
- No dataset was attached, and the brief depends on data. Finding or generating it is part of the work.
- Known obstacles in the brief: Needs hardware.

## 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 Coal'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 (479 words)

Background: Surface subsidence caused by underground coal mining poses significant risks to nearby communities, public infrastructure, agricultural land, forest areas, and the surrounding environment. In India, subsidence monitoring is still largely dependent on conventional field observations, periodic surveys, and post facto damage assessments, which often fail to provide timely warning before critical ground failure occurs. There is a strong need for an indigenous, low cost, intelligent, and real time monitoring solution capable of detecting early signs of ground movement and enabling proactive risk mitigation. Such a system should be affordable, scalable, and deployable across Indian underground coal mines using widely accessible technologies, thereby supporting the national vision of smart and sustainable mining. Description: The problem envisages development of an AI-enabled smart mine subsidence monitoring and early warning platform based on a localized wireless surface mesh sensor network deployed above underground mine panels. The proposed solution involves installing a distributed network of low cost smart sensor nodes across the surface over the underground mining area. Each node may be equipped with sensors such as: • tilt/inclination sensors, • vibration sensors, • displacement/stretch sensors, • crack detection sensors, • optional low cost positioning modules. These nodes will communicate through a wireless mesh communication network (such as LoRa/Zigbee/Wi-Fi mesh), enabling continuous real time monitoring of micro ground movements over the mine panel. The system should continuously detect: • abnormal ground tilt, • change in relative distance between nodes, • early crack initiation, • unusual vibration signatures, which may indicate the onset of subsidence. Using Artificial Intelligence / Machine Learning, the platform should: • identify abnormal deformation patterns, • predict possible subsidence zones, • estimate severity and progression, • generate automated early warning alerts, • support timely operational decisions. The solution should be robust, low power, scalable, and suitable for Indian geo-mining conditions. Expected Solution: A web/mobile enabled intelligent mine subsidence monitoring platform integrating IoT, wireless mesh networking, AI, and GIS technologies for: • development of low cost smart sensor nodes using readily available hardware platforms (e.g., Arduino/ESP32/Raspberry Pi); • deployment of a localized wireless mesh network over underground mine panels for continuous surface deformation sensing; • real time monitoring of tilt, displacement, vibration, and crack initiation; • AI/ML-based anomaly detection and subsidence prediction using live and historical data; • GIS based visualization of live deformation maps and risk zones; • automated early warning alerts through SMS/email/mobile app notifications; • interactive dashboards for mine operators, planners, and regulators; • offline capability with periodic cloud synchronization; • scalable deployment across multiple underground coalfields. The proposed solution must be low cost, easy to deploy, energy efficient, scalable, and student prototype friendly, while enabling a Made in India smart mining safety solution for sustainable underground coal mining. Now your problem statement has a clear unique innovation hook: 'Wireless Surface Mesh Network for Real Time Subsidence Detection' that is what will differentiate it from generic AI proposals.