JEEVHITAA -- An End-to-End HCAI System to Support Collective Care

• URL: http://arxiv.org/abs/2512.06364v2
• Date: Wed, 10 Dec 2025 17:26:03 GMT
• Title: JEEVHITAA -- An End-to-End HCAI System to Support Collective Care
• Authors: Shyama Sastha Krishnamoorthy Srinivasan, Harsh Pala, Mohan Kumar, Pushpendra Singh,
• Abstract summary: We presentVHITAA, an Android/Flutter system that provides context-sensitive, role-aware sharing and verifiable information flows for care circles.<n>VHITAA ingests platform and device data (via Google Health and BLE connectors), constructs multi-layer user profiles from sensor streams and tiered, and enforces fine-grained, time-bounded access control across permissioned care graphs.
• Score: 5.456792874544804
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Current mobile health platforms are predominantly individual-centric and lack the necessary primitives for coordinated, auditable, multi-actor workflows. However, in many settings worldwide, health decisions are enacted by multi-actor care networks rather than single users. We present JEEVHITAA, an Android/Flutter system that provides context-sensitive, role-aware sharing and verifiable information flows for care circles. JEEVHITAA ingests platform and device data (via Google Health Connect and BLE connectors), constructs multi-layer user profiles from sensor streams and tiered onboarding, and enforces fine-grained, time-bounded access control across permissioned care graphs. Data are end-to-end encrypted in local stores and during peer sync (Firebase), and provisions are made for document capture by camera or upload as PDF. An integrated retrieval-augmented LLM pipeline (i) produces structured, role-targeted summaries and action plans, (ii) enables users to gather advanced insights on health reports, and (iii) performs evidence-grounded user-relevant verification of arbitrary health content, returning provenance, confidence scores, and source citations. We describe the system architecture, connector abstractions, and security primitives, and evaluate robustness and compatibility using synthetic, ontology-driven simulations and vendor compatibility tests. Finally, we outline plans for longitudinal in-the-wild deployments to measure system performance, the correctness of access control, and the real-world effectiveness of relationship-aware credibility support.

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