Proposed AI solution for accessible emergency services
Despite multiple access channels under India’s ERSS-112, persons with disabilities still face major barriers in emergencies, such as no real-time sign language support, limited deafblind-friendly interfaces, weak AI interpretation, and difficulties in multilingual or high-stress situations, leading to delays, miscommunication, or exclusion.
Key challenges
No real‑time sign language or visual relay support
Limited reliability in low‑connectivity environments
Multilingual and accent‑related communication complexity
The solution
Multimodal communication
Speech‑to‑text and text‑to‑speech
Conceptual sign language avatar support
Gesture‑based and intent‑driven inputs
Haptic feedback for deafblind users
Planned support for 10+ Indic languages
Intelligent assistance
Automatic location detection (sensor fusion)
AI‑assisted call summaries for operators
Emergency intent classification
Noise‑robust speech recognition
1
Community onboarding
Collaboration with disability‑focused NGOs
Accessibility awareness workshops
Multilingual user onboarding strategy
Inclusive app design and rollout plan
2
System integration
API‑based integration with ERSS‑112
Panic and silent‑mode design considerations
Hybrid cloud and on‑device deployment model
Offline and low‑bandwidth fallback mechanisms
3
Capability building
Operator training concepts
Continuous feedback loops
Accessibility‑focused UI/UX design
Bias mitigation and inclusivity testing
Targeted communication efficiency
Targeting significantly faster information exchange
Reduced delays caused by repeated clarifications
Improved real‑time interaction for PwDs
Reduced operator cognitive load
AI‑generated summaries to support faster decision‑making
Reduced misinterpretation through multimodal inputs
More structured emergency information flow
Anticipated user acceptance
Designed for deaf, blind, speech‑impaired, deafblind, and cognitively disabled users
Haptic, visual, and low‑literacy‑friendly interfaces
Inclusive, dignity‑preserving interaction design
Deployment plan
Pilot for up to 500 users in one urban region
Expansion to additional states and user groups
Design readiness for 10,000+ nationwide users
Scale impact
Open-source select components for wider adoption
Continuous model improvement (sign language, bias, multilingual)
Stronger NGO and government partnerships
Note: EAR is currently in the proposal stage. All impact metrics represent projected targets, based on system design goals and global best practices, and are subject to validation during pilot execution.
