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SilverLink — Neighbour-to-Neighbour Care Network

A voice-first app that connects elderly and OKU residents with verified neighbours for everyday help and SOS.

VISUAL SHOWCASE & DEMONSTRATION
3 MEDIA ATTACHMENTS
MEDIA_STAGE // 1 OF 3
VIDEO DEMO
💬 SilverLink: Connecting Neighbours, Caring for EldersSLOT_1
THE PROBLEM STATEMENT // CHALLENGE

Elderly residents in high-rise townships often cannot reach daily necessities because of mobility limits or lift breakdowns, and those living alone may have a fall that nobody notices. Property management looks after facilities but not personal needs, and working family members are away during the day. Gig apps send strangers and charge per task, and most apps assume users can read small text and handle multi-step flows.

THE ARCHITECTURAL SOLUTION

SilverLink matches elderly and OKU residents with verified neighbours in the same township for short, non-medical help such as meal pickups, groceries and wellness checks. A multilingual AI voice assistant ("Kawan SilverLink") lets users make requests, hear what's on the screen and trigger SOS just by speaking. A one-tap SOS, a daily check-in, and Community Points that can offset maintenance fees round out the system.

SYSTEM ARCHITECTURE & DESIGN PATTERNS
[1]Elder speaks or taps a request in the Android app; on-device speech recognition converts the voice to text, and SOS keywords are checked locally first.
[2]The backend AI service (Gemini with Groq fallback) turns the request into a structured action through whitelisted tool calls, and asks the user to confirm.
[3]The matching engine sends the request to verified helpers nearby; the first helper to accept gets the task.
[4]Live task status, GPS tracking and chat run over Socket.IO, with FCM, SMS and voice-call escalation for SOS and missed check-ins.
[5]The admin web console handles resident verification, the live SOS board, disputes and Community Points rewards.
TECHNICAL HURDLES OVERCOME

The hardest part was designing for users who may not be able to read small text, type, or follow multi-step flows. This led to a voice-first flow, four UI modes (Senior Simple, Accessibility/OKU, Standard and Admin) and high-contrast and colour-blind-safe themes. Balancing trust and privacy (resident verification, PDPA consent, no medical advice from the AI) while keeping every step simple took several design iterations.

KEY OUTCOMES & IMPACT

The full system plan, an interactive Figma prototype covering the core workflows, and a 5-minute promo video showing real-life scenarios were completed for the INNOVA-X (UTeM) SDP Hackathon. Android development is in progress, and the backend and admin console are next.

TECH ARSENAL (INVENTORY)
FigmaKotlinJetpack ComposeNode.jsTypeScriptExpressPostgreSQLPrismaRedisSocket.IOFirebase (AuthFCM)Gemini APIReact
QUEST TELEMETRY
QUEST ID:#quest-1792843625958
RANK:A-Rank
CATEGORY:Mobile
MEDIA ASSETS:3 Items
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