Development of A Voice-Controlled Smart Home System for Elderly and Disabled Individuals

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The increasing global population of older adults and people with disabilities has intensified the demand for assistive technologies that enhance independent living. While commercially available smart home systems provide voice-controlled automation, most rely heavily on cloud-based speech processing, thereby requiring stable internet connectivity and raising concerns regarding latency, affordability, and data privacy. This study presents the design, development, and experimental validation of an offline voice-controlled smart home system tailored for resource-constrained environments. The system employs an ESP32 microcontroller integrated with an embedded speech recognition engine that processes commands locally, without internet dependency. A structured V Model development lifecycle was adopted to ensure systematic hardware–software integration and validation. Performance evaluation was conducted using recognition accuracy, response time, false activation rate, and system reliability metrics. Experimental results indicate a recognition accuracy of 91.3% under quiet conditions and 86.7% in moderate noise environments, with an average response time of 1.4 seconds. The system maintained 99.2% operational uptime during continuous testing. The findings demonstrate that offline embedded voice-controlled architectures provide a cost-effective, privacy-preserving, and reliable assistive solution suitable for developing regions.