International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | PAWCAREAI: An Intelligent AI-Driven Platform for Comprehensive Pet Care Management |
|---|---|
| ABSTRACT | The intersection of artificial intelligence (AI) and the rapidly expanding pet care industry presents a unique opportunity to transform the way pet owners manage the health, welfare, and daily needs of their companion animals. This paper presents PAWCAREAI, a unified, AI-powered mobile platform that consolidates five critical dimensions of pet care into a single, intuitive application: dedicated pet profile management, an integrated pet product e-commerce module, personalised AI chatbots contextualised to each user's individual pet, intelligent daily reminders for vaccinations and routine activities, and a geolocation-based veterinary clinic locator. The platform leverages large language model (LLM) technology for conversational intelligence, push-notification scheduling for proactive health reminders, and Google Maps APIs for real-time veterinary proximity search. We describe the system architecture, module interactions, and design rationale in detail. Against the backdrop of a global pet care market valued at over USD 190 billion in 2024 and projected to exceed USD 323 billion by 2033, PAWCAREAI addresses a clear gap: the absence of a holistic, AI-augmented digital companion for pet owners. User trials across a pilot cohort demonstrated measurably improved vaccination compliance, reduced time-to-information for health queries, and increased engagement with preventive care practices. PAWCAREAI represents a meaningful step toward AI-augmented, proactive pet wellness management. |
| AUTHOR | PROF. MANJULA P, ROHAN K JOE, SRUJAN KUMAR MD, SYED ABU TALHA, SHAMANTH KUMAR M, SANDESH KUMAR S Assistant Professor, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India UG Students, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India |
| VOLUME | 184 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1405085 |
| pdf/85_PAWCAREAI An Intelligent AI-Driven Platform for Comprehensive Pet Care Management.pdf | |
| KEYWORDS | |
| References | [1] American Pet Products Association (APPA). (2025). APPA 2025 State of the Industry Report. Greenwich, CT: APPA. [2] Grand View Research. (2025). Pet Care Market Size, Share & Growth Report, 2026–2034. San Francisco: Grand View Research. [3] Straits Research. (2025). Pet Care Market Size, Share & Growth Graph by 2034. New York: Straits Research. [4] Zion Market Research. (2025). Global Pet Care Market Size, Share, Analysis, Growth & Trends 2034. Sarasota: ZMR. [5] Future Market Insights. (2025). Pet Care Market Analysis & Forecast 2025–2035. Newark: FMI. [6] Cascadia Capital. (2024). Pet Industry Overview Report: AI, Data, and the Future of Pet Care. Seattle: Cascadia Capital. [7] Teng, Z., & Gomez, R. (2025). Artificial intelligence and companion animals: Perspectives on digital healthcare for dogs, cats, and pet ownership. ScienceDirect / Computers and Electronics in Agriculture, 221, 109892. [8] Washington Post. (2024, June 7). How smart pet technology and AI are helping (and possibly harming) pets. Washington, D.C.: The Washington Post. [9] DataRoot Labs. (2025). AI-Powered Pet Care: Health Monitoring, Smart Feeders, and Virtual Vet Support. Kyiv: DataRoot Labs. [10] Chu, C. P. (2024). ChatGPT in veterinary medicine: a practical guidance of generative artificial intelligence in clinics, education, and research. Frontiers in Veterinary Science, 11, 1395934. https://doi.org/10.3389/fvets.2024.1395934 [11] Jokar, M., et al. (2024). AI chatbots in pet health care: Opportunities and challenges for owners. Veterinary Medicine and Science, 10(3), e1464. https://doi.org/10.1002/vms3.1464 [12] TUUL.AI Research. (2024). What We Learned Building Our First LLM-Based App: AVVA. Tallinn: TUUL.AI. [13] PetDesk Inc. (2025). PetDesk: Pet Health Reminders Application. San Diego: PetDesk. [14] VitusVet Inc. (2025). VitusVet: Pet Health Care App. Austin: VitusVet. [15] Boop Pet Limited. (2025). Boop – Making Pet Care Digital. United Kingdom: Boop Pet. [16] ResearchGate. (2025). Pet's Mind: An AI-Powered Mobile Application for Pet Care, Health Tracking, and Community Support. Berlin: ResearchGate GmbH. [17] Grand View Research. (2025). Pet Services Market Size, Share | Industry Report, 2033. San Francisco: Grand View Research. [18] Technavio. (2025). Pet Care Market Forecast 2025–2029. London: Technavio / Infiniti Research. [19] Cascadia Capital. (2024). 2024 Pet Industry Overview: AI Immersion Across Every Pet Segment. Seattle: Cascadia Capital. [20] World Small Animal Veterinary Association (WSAVA). (2022). WSAVA Vaccination Guidelines 2022. Geneva: WSAVA. [21] Xiao, L., et al. (2025). Review of applications of deep learning in veterinary diagnostics and animal health. Frontiers in Veterinary Science, 12, 1558832. [22] Business Wire. (2025, January 3). Traini Launched the World's First Generative AI for Pets. New York: Business Wire. [23] Fortune Business Insights. (2025). Pet Care Market Size, Share | Industry Report, 2026–2034. Pune: Fortune Business Insights. |
