From Papers to Products
CAM-AI RPS focuses on building real AI solutions for real problems.
The scheme promotes innovative, AI-driven, multidisciplinary research aimed at deployable solutions, startup potential, and institutional transformation. Projects are expected to produce working prototypes, applications, AI tools, or deployable systems within the sanctioned period.
1. Introduction
CAM-AI Research Projects Schemes (CAM-AI RPS) aims to promote innovative, AI-driven research solutions to enhance campus governance, academic excellence, and institutional efficiency. The scheme provides Minor and Major research grants to eligible faculty members to promote original, innovative, and AI-driven multidisciplinary research, with a strong focus on developing intelligent, application-oriented solutions and deployable AI products.
Each project should contribute toward deployable solutions, startup potential, and institutional transformation rather than only academic outputs. Projects must demonstrate working prototypes, applications, AI tools, or deployable systems within the sanctioned period. Selection will be based on the strength of the idea, clarity of vision, technical feasibility, and execution capability within the defined timeline.
2. Objectives of CAM-AI RPS
- To promote AI-driven innovation for solving real-world, University, and societal problems.
- To foster a product-oriented research ecosystem focused on deployable AI applications and tools.
- To enable rapid prototyping and implementation within a defined timeframe.
- To encourage interdisciplinary collaboration integrating domain knowledge with AI technologies.
- To develop scalable, impactful AI solutions with real-world usability.
- To support startup potential, innovation, and institutional transformation through AI.
3. Types of Grants Offered
Under CAM-AI RPS, two categories of research grants are offered to support AI-driven, product-oriented innovation. A Principal Investigator (PI) can submit only one proposal in total, and that too in either Major or Minor category, but not both.
Major Research Projects
- Designed for high-impact, scalable AI solutions
- Focus on advanced development and deployment-ready systems
- Maximum Funding: ₹10 Lakhs
- Expected Outcome: Fully functional AI product or working prototype with strong implementation potential
- Duration: Maximum 12 months
Minor Research Projects
- Designed for pilot studies, prototypes, and early-stage innovations
- Focus on idea validation and initial development
- Maximum Funding: ₹5 Lakhs
- Expected Outcome: Working prototype or proof-of-concept AI solution
- Duration: Maximum 06 months
4. Who Can Apply
Faculty members of University Campus with demonstrated interest or execution capability in Artificial Intelligence, Machine Learning, Data Science, or related domains are eligible to apply.
- Eligibility criteria remain common for both categories.
- The distinction is based on scale, complexity, funding requirement, and expected output, not on prior publications or experience.
- The PI or Co-PI must possess a basic understanding or demonstrable interest in AI, ML, or Data Science.
- The proposal must be clear, product-oriented, and focused on application, development, and deployment, not purely theoretical work.
- The proposal must define a real-world, institutional, or societal problem statement clearly.
Additional Project Requirements and Preferences
- Preference for multidisciplinary collaboration across departments
- Preference for proposals including industry or external partnerships
- Preference for readiness toward prototype development or early-stage implementation
- Preference for strong innovation potential, practical applicability, and scalability
5. Expected Project Outcomes
Each funded project must deliver at least one functional AI-based product or working prototype, such as:
AI Application
Web or mobile AI application for practical deployment.
AI Agent / Chatbot
Interactive systems for automation, support, or assistance.
AI Dashboard / Decision System
Analytics or decision-support products for institutional use.
Prototype
Hardware, IoT, drone, robotics, or other implementation-ready AI prototypes.
AI Tool / Software Platform
Standalone tools or platforms with practical product potential.
Note: Publications and patents are desirable outputs.
6. Priority Research Themes
Including but not limited to the following:
1. AI in Education & Learning Analytics
Student performance prediction, personalized learning, automated evaluation, question paper generation, dropout prediction, and learning analytics.
Expected Outcomes: Adaptive learning app, AI evaluation tool, performance dashboard, AI tutor chatbot.
2. AI in Healthcare & Medical Applications
Disease prediction, medical image analysis, patient monitoring, mental health analysis, biological sciences, and public health data analytics.
Expected Outcomes: Disease prediction web app, AI MRI/X-ray analyzer, patient dashboard, diagnosis assistant.
3. AI for Smart Campus / Smart City
Attendance systems, surveillance analytics, traffic and parking optimization, energy management, waste management, and water optimization.
Expected Outcomes: Face-recognition attendance, smart parking app, AI surveillance dashboard, IoT waste system.
4. AI in Governance & Administration
AI chatbots, file tracking, decision support, document automation, grievance redressal, and administrative analytics.
Expected Outcomes: University services chatbot, file tracking AI, document auto-processing tool, grievance portal.
5. AI in Agriculture & Rural Development
Crop disease detection, yield prediction, soil analysis, smart irrigation systems, and rural data-driven decision systems.
Expected Outcomes: Crop disease app, AI yield predictor, soil analysis tool, rural advisory chatbot.
6. AI in Business, Finance & Commerce
Financial forecasting, fraud detection, customer behavior analysis, marketing analytics, and supply chain optimization.
Expected Outcomes: Fraud detection system, forecasting dashboard, customer analytics engine, AI marketing tool.
7. AI in Law, Ethics & Policy
Legal document analysis, cybercrime detection, AI ethics and bias studies, data privacy frameworks, and policy analysis systems.
Expected Outcomes: Legal document analyzer, cybercrime tool, compliance checker, privacy risk analyzer.
8. AI for Social Sciences & Behavioral Studies
Sentiment analysis, behavioral prediction, education psychology applications, survey analytics, and social impact assessment.
Expected Outcomes: Sentiment analysis tool, behavioral model, survey analytics dashboard, social impact tool.
9. AI with Robotics, IoT & Drones
Autonomous drones, robotics automation, computer vision systems, IoT-based smart systems, and intelligent navigation or control systems.
Expected Outcomes: Robotics and IoT enabled intelligent systems and deployable prototypes.
10. Generative AI & Emerging Technologies
LLM-based applications, chatbots, AI assistants, content generation systems, multimodal AI, and AI-driven automation tools in fine and performing arts.
Expected Outcomes: LLM chatbot, AI content generator, multimodal AI app, academic or admin AI assistant.
7. Submission Guidelines
Proposal Format
Maximum 5 pages, single side, Headings in Arial 13 bold, text in Arial 12, single line spacing.
- Project Title - clear and concise, maximum 2 lines
- Introduction - problem background, relevance, and objectives
- Literature Review - brief review with key references
- Justification - need, novelty, and application potential
- Methodology - approach, tools, and implementation plan, AI-based
- Timeline - phase-wise plan for 12 months
- Facilities Available / Required
- Equipment Details
- Collaborations - academic or industry partners, if any
- Expected Outcomes - product-oriented deliverables
- Budget - with proper justification
- Declaration - by PI and Head of Department
Note: The proposal must clearly demonstrate innovation, feasibility, and delivery of a functional AI-based product or working prototype.
Mandatory Video Presentation
- A 5 to 7 minute recorded video presentation must be submitted.
- The video should cover problem statement, methodology, innovation, outcomes, and budget in brief.
- Format: MP4 file or shareable link such as Google Drive or unlisted YouTube link.
- The presentation should normally be delivered by the Principal Investigator.
Submission Process
- Step 1: Online submission through the University Portal / Google Form
- Step 2: Submission of two hard copies of the complete proposal to the Office of the Dean, Research & Development
8. Mandatory Documents / Downloads
9. Evaluation and Monitoring
- All proposals will be evaluated by a University-appointed Expert Committee.
- After completion of the project, a Final Report must be submitted.
- A functional AI product or prototype demonstration is required.
- Utilization Certificate must be submitted.
- All publications arising from the project must acknowledge funding under CAM-AI Research Project Scheme (CAM-AI RPS), CSJM University.
10. Important Instructions
- Submission of all documents and video presentation is mandatory.
- Incomplete applications or missing documents or video will be rejected.
- The submission will be treated as final, and no modifications will be allowed after the deadline.