Operation Ward Zero

Build a Hospital That Fits Inside a Bedroom

About the Hackathon:

What if a patient's bedroom could function like a smart hospital ward?

Hospitals have monitoring systems, trained healthcare professionals, and alert mechanisms to detect changes in patient conditions. At home, however, patients often depend on family members and caregivers who may not have access to continuous monitoring or early-warning systems.

Operation Ward Zero is an online healthcare technology hackathon inviting innovators, developers, and problem-solvers to design intelligent home healthcare solutions.

Participants will develop a working prototype demonstrating how IoT simulation, full-stack applications, and AI/ML can work together to monitor patient conditions, identify potential risks, and support timely caregiver responses.

The central mission is:

Sense → Understand → Predict → Alert → Respond

Participants are encouraged to develop practical, affordable, scalable, and user-friendly solutions that address real-world home healthcare challenges.

No physical hardware is required. Participants may use simulated sensors, synthetic patient data, mock devices, and software-based environments.

Eligibility Criteria:

• Open to students, recent graduates, aspiring developers, and technology enthusiasts interested in healthcare innovation.
• Participants from engineering, computer science, information technology, data science, artificial intelligence, and related disciplines are encouraged to participate.
• Team Size: Minimum 2 and maximum 3 members.
• Inter-college teams: Allowed. Participants from different colleges or institutions may form a team.
• Inter-specialization teams: Allowed. Participants from different academic branches, specializations, or technical backgrounds may collaborate.
• Each participant may belong to only one team.
• Each team must nominate one team leader responsible for registration, coordination, and final submission.
• Participants should possess basic technical knowledge relevant to their chosen solution.

Competition Structure and Format:

Number of Problem Statements: 1 overarching problem statement covering IoT, Full Stack, and AI/ML.

Competition Format: Single-round project submission and evaluation.

Round 1: Prototype Development and Submission

Participants must develop and submit a working prototype addressing the official problem statement.

The submission must demonstrate how the proposed system collects or simulates patient data, processes information, identifies risks, generates alerts, and enables caregiver responses.

Submission Deadline: 24 October 2026

Participants must submit their solution through the official Wooble challenge page.

Round 2: Evaluation and Results:

All eligible submissions will be evaluated by the designated reviewers based on predefined technical and practical evaluation criteria.

There is no separate live presentation or physical evaluation round specified.

Results Announcement: 31 October 2026

Winners will be selected based on their overall evaluation scores and compliance with the competition guidelines.

Problem Statement:

Build an Intelligent Home Healthcare Monitoring and Response System

Design and develop a software-based healthcare monitoring solution that demonstrates how a patient's home can operate like a small, intelligent hospital ward.

The proposed solution should illustrate the following workflow:

Patient Data → Monitoring Platform → Risk Assessment → Alert Generation → Caregiver Response

Participants may address one or more of the following challenges:

• Patient Monitoring: Simulate and monitor patient vitals such as heart rate, oxygen saturation, blood pressure, and temperature.
• Caregiver Monitoring: Develop mechanisms to track caregiver attendance, activity, and response to alerts.
• System Reliability: Demonstrate how the system handles connectivity interruptions, delayed data transmission, or temporary service failures.
• Contextual Intelligence: Combine patient vitals, historical information, and caregiver notes to support risk assessment.
• Predictive Analytics: Explore AI/ML techniques to identify possible patient deterioration 24–48 hours in advance.
• Alert and Escalation: Develop a system that categorizes risks and notifies the appropriate caregiver or responsible person.

Participants are not required to build a production-ready medical device or clinically validated diagnostic system.

The objective is to demonstrate technical capabilities, problem-solving skills, integration, and practical thinking through a functional prototype.

Technical Tracks:

Participants may contribute through one or more of the following technical areas:

IoT Development:

• Simulated sensors and patient monitoring devices.
• Collection and transmission of patient data.
• Device communication and monitoring workflows.

Full Stack Development:

• Patient monitoring dashboards.
• Data visualization and application interfaces.
• Caregiver alert and acknowledgment systems.
• Backend services, databases, and APIs.

AI/ML Engineering:

• Patient risk classification.
• Identification of unusual patterns.
• Analysis of patient context and caregiver notes.
• Explainable risk predictions and alerts.

Teams are encouraged to demonstrate end-to-end integration, but participants are not expected to be experts in every technical domain.

Mandatory Submission Requirements:

Each team must submit the following deliverables:

A. Working Prototype:

A functional demonstration showing patient data collection or simulation, platform processing, risk detection, alert generation, and caregiver acknowledgment.

B. Source Code Repository:

A GitHub or GitLab repository containing:

• Source code.
• README documentation.
• Installation and setup instructions.
• Required dependencies and configurations.
• Sample or synthetic datasets, where applicable.

C. Technical Documentation:

A document explaining:

• Problem understanding and proposed solution.
• System architecture and technology stack.
• Major features and functionality.
• Data processing and risk assessment approach.
• Assumptions, limitations, and future improvements.

D. Demonstration Video:

A video of approximately 3 minutes, demonstrating the complete workflow:

Sensor Simulation → Platform → AI Risk Detection → Alert → Caregiver Response.

Important: Physical hardware is not mandatory. Software simulators, mock sensors, and synthetic datasets are permitted.

Evaluation Criteria:

Submissions will be evaluated using the following weighted criteria:

Evaluation Parameter

Weightage

End-to-End Integration

25%

Technical Skills

20%

Reliability & Resilience

20%

Practical Implementation

20%

Explainability & Clinical Safety

15%

Total

100%

End-to-End Integration (25%): How effectively the proposed components communicate and function as a unified system.

Technical Skills (20%): Quality of implementation, architecture, programming practices, and appropriate use of technology.

Reliability & Resilience (20%): Ability to handle failures, unexpected conditions, and interruptions.

Practical Implementation (20%): Usability, feasibility, completeness, and relevance to real-world home healthcare.

Explainability & Clinical Safety (15%): Clarity of risk explanations, responsible handling of healthcare information, and avoidance of unsafe or unsupported medical claims.

Prizes and Recognition:

Total Cash Prize Pool: ₹10,000

• 1st Position: ₹5,000
• 2nd Position: ₹3,000
• 3rd Position: ₹2,000

Additional Opportunities:

• 3 internship opportunities with potential Pre-Placement Offers (PPOs), subject to selection and organizational requirements.
• Verifiable participation certificates for eligible participants who successfully submit their work.
• Opportunity to demonstrate technical skills to industry reviewers and the organizing company.

A PPO is not guaranteed and depends on internship performance, organizational requirements, and applicable selection criteria.

Rules and Regulations:

• All participants must register and submit their projects through the designated official platform within the announced deadline.
• Each team must consist of 2–3 members. A participant cannot be part of multiple teams.
• Inter-college and interdisciplinary collaboration is permitted.
• Each team may submit only one final solution.
• Submissions must represent the team's own meaningful technical contribution. Existing open-source libraries, frameworks, pretrained models, and APIs may be used with appropriate acknowledgment and license compliance.
• Plagiarism, unauthorized copying, fabricated results, or misrepresentation of functionality may result in disqualification.
• AI-assisted development tools are permitted, provided the team understands and can explain its implementation.
• Teams must provide accessible source code, functional demonstration material, and the required documentation.
• Participants must not use real patient information without appropriate authorization. Synthetic or anonymized data is strongly recommended.
• The developed solution must be treated as an experimental prototype and must not make unsupported claims about medical diagnosis, treatment, or clinical accuracy.
• Participants are responsible for ensuring that submitted materials do not infringe third-party intellectual property rights.
• Incomplete, inaccessible, or late submissions may be rejected.
• Evaluation will be based on the published criteria, and the judging panel's decision will be final regarding competition rankings.
• The organizing team may verify submissions, request clarification, or investigate suspected rule violations.
• Participants retain ownership of their original work, subject to the licenses and rights of any third-party components they use.
• Any changes to the competition schedule or guidelines will be communicated through official organizer channels.

Official Submission Platform:

All project submissions and challenge-related information are available on Wooble.

Challenge Link:

https://wooble.org/companies/nursio-innovation-pvt-ltd-2/challenges/operation-ward-zero

Build technology that helps caregivers respond earlier, patients feel safer, and home healthcare become smarter.