Ongoing Research
AI SENSE is an R&D-focused venture at the intersection of nature and technology. We design, build, and deploy intelligent systems that bridge natural environments with digital sensing tools — applying edge AI and nature-inspired algorithms to support sustainable, data-driven decisions in agriculture, biodiversity monitoring, and climate resilience.
This page outlines our currently active funded projects, research areas, and collaborating institutions. For completed work and publications, see Completed Researches.
Active Funded Projects
NSF SBIR Phase I — AI CoExist
Funder: National Science Foundation (NSF), Small Business Innovation Research Programme
Topic: Wildlife detection and adaptive deterrence for farming communities
Period: 2025 – Present
AI CoExist integrates AI-enabled cameras with a detect–deter–adapt feedback loop to detect, classify, and track wildlife species in real time, enabling humane coexistence between farmers and local ecosystems. This project represents our flagship funded research initiative.
USDA Collaborative Projects
Funder: United States Department of Agriculture
Topic: Precision agriculture, crop loss quantification, disaster response
Period: 2024 – Present
In partnership with USDA and land-grant universities, we are developing AI-driven tools for rapid agricultural damage assessment using satellite, UAV, and IoT sensor data. Research outputs include open datasets and policy briefs.
Current Research Areas
Our active research spans the following domains:
- Wildlife detection and humane deterrence (computer vision, acoustic sensing)
- Agricultural disaster response (satellite + UAV + IoT data fusion)
- Urban farming AI monitoring (crop health, environmental sensing)
- Edge AI and TinyML for resource-constrained outdoor environments
- Federated learning for distributed sensor networks
- Acoustic sensing and biodiversity monitoring
- Climate-smart agriculture and climate resilience modelling
- Human–wildlife conflict mapping and spatial ecology
University Collaborators
We maintain active research relationships with the following institutions:
- University of Maryland, College Park (UMD)
- University of Maryland Baltimore County (UMBC)
- University of Maryland Eastern Shore (UMES)
Collaborating Researchers
The following faculty and researchers contribute expertise to our ongoing projects:
Dr. Nirupam Roy
Assistant Professor, Department of Computer Science, University of Maryland, College Park.
Expertise: Acoustic sensing systems, mobile computing, human–computer interaction.
Dr. Anuradha Ravi
Research focus: Edge AI, federated learning, and distributed inference for IoT networks.
Contributing to our TinyML optimisation pipeline and privacy-preserving field sensing research.
Dr. Travis Gallo
Urban ecologist and conservation scientist.
Expertise: Human–wildlife coexistence, urban biodiversity, applied spatial ecology.
Advising on ecological validity of AI CoExist deterrence outcomes.
Dr. Nirmalya Roy
Professor and COO, AI SENSE. Director, Mobile, Pervasive, and Sensor Computing Lab, UMBC.
Expertise: Pervasive computing, wireless sensor networks, smart environments, activity recognition.
Grant Collaboration
We welcome proposals for joint research and collaborative grant applications. AI SENSE can serve as a commercial co-applicant or technical partner on federal grants (NSF, USDA, DARPA, NIH, DOE) and international programmes. Our strengths include:
- Hardware prototyping and field deployment of sensing systems
- Annotated wildlife and agricultural datasets
- Edge AI inference pipelines and TinyML expertise
- Access to field sites in the US (Maryland) and South Asia (Nepal)
- Industry co-funding or cost-share contributions for SBIR / STTR proposals
To discuss a collaboration, email us at [email protected] with a brief description of your research goals and timeline.
Contact for Research Enquiries
For research collaborations, joint grants, dataset requests, or invited talks:
Email: [email protected]
PI: Dr. Nirmalya Roy, COO — [email protected]
Address: AI SENSE USA, Baltimore, MD 21250
We aim to respond to all research enquiries within 3–5 business days.