This paper explores the design and implementation of a voice-controlled smart home system utilizing the Raspberry Pi platform and Node.js framework. The system aims to provide users with an intuitive method for managing household devices through voice commands while enhancing functionality with integrated sensors. Leveraging the Hidden Markov Model Toolkit (HTK) for speech recognition, the system accurately interprets user commands, facilitating control over lighting, temperature, and various IoT devices. In addition to voice activation, the system incorporates multiple sensors: a temperature sensor for monitoring ambient conditions, a motion sensor (PIR) for detecting occupancy, and a light sensor for assessing natural light levels. These sensors work in harmony with the voice control features, enabling automated responses such as adjusting the heating or cooling based on temperature readings, activating lights upon detecting movement, and regulating artificial lighting according to available daylight. Comprehensive testing demonstrated the system’s high accuracy in command recognition and its responsiveness to user inputs, as well as its robust integration with additional smart devices. User feedback was instrumental in refining the system, leading to improvements in command clarity and operational efficiency. This research highlights the potential of combining voice control and sensor technology to create a more responsive and user-friendly smart home environment.
This paper provides a concise overview of Agile and DevOps methodologies in software engineering. It aims to introduce readers to the fundamental principles of Agile and DevOps, accompanied by brief descriptions and practical examples. The advantages and disadvantages of each methodology are discussed, followed by a comparative analysis highlighting key differences. Understanding these methodologies is crucial in today’s IT landscape, as they are commonly employed in various organizations, impacting project management, team collaboration, and product delivery. This paper serves as a valuable resource for individuals seeking a basic understanding of Agile and DevOps methodologies in software engineering.
This paper explores the design and implementation of a voice-controlled smart home system utilizing the Raspberry Pi platform and Node.js framework. The system aims to provide users with an intuitive method for managing household devices through voice commands while enhancing functionality with integrated sensors. Leveraging the Hidden Markov Model Toolkit (HTK) for speech recognition, the system accurately interprets user commands, facilitating control over lighting, temperature, and various IoT devices. In addition to voice activation, the system incorporates multiple sensors: a temperature sensor for monitoring ambient conditions, a motion sensor (PIR) for detecting occupancy, and a light sensor for assessing natural light levels. These sensors work in harmony with the voice control features, enabling automated responses such as adjusting the heating or cooling based on temperature readings, activating lights upon detecting movement, and regulating artificial lighting according to available daylight. Comprehensive testing demonstrated the system’s high accuracy in command recognition and its responsiveness to user inputs, as well as its robust integration with additional smart devices. User feedback was instrumental in refining the system, leading to improvements in command clarity and operational efficiency. This research highlights the potential of combining voice control and sensor technology to create a more responsive and user-friendly smart home environment.
