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By the virtue of blooming automation industry and wireless connectivity, all the devices within the home can be connected. This improves the comfort, energy efficiency, indoor security and cost savings of the home. Small and constrained embedded devices are used to remotely monitor the conditions within home and control the home appliances. In such case, power consumption and network bandwidth become a major concern. We need a low power device that transmits messages through a less verbose protocol.There are a wide variety of technology platforms, or protocols, on which a smart home can be…mehr

Produktbeschreibung
By the virtue of blooming automation industry and wireless connectivity, all the devices within the home can be connected. This improves the comfort, energy efficiency, indoor security and cost savings of the home. Small and constrained embedded devices are used to remotely monitor the conditions within home and control the home appliances. In such case, power consumption and network bandwidth become a major concern. We need a low power device that transmits messages through a less verbose protocol.There are a wide variety of technology platforms, or protocols, on which a smart home can be built. Each one is, essentially, its own language. Each language speaks to the various connected devices and instructs them to perform a function. The work is based on light weight Message Queuing Telemetry Transport (MQTT) protocol. The central communication point is the MQTT broker, it is in charge of dispatching all messages between the senders and the rightful receivers. Publish/Subscribe, event-driven technique enables messages to be pushed to the clients. In the protocol, we attempt to implement MQTT on Raspberry PI, a Wi-Fi based development board.
Autorenporträt
Dr. Smitha Shekar B and Dr. Harish G are currently Associate Professors working with Department of Computer Science & Engineering, Dr. Ambedkar Institute of Technology, Bangalore. Their current research interests include Wireless Sensor Networks, IoT , VANETs and Machine Learning.