Efficient energy consumption data collection and processing with wireless sensors and cloud

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Rimeware Technologies Inc. is a product and service provider of monitoring and modeling energy consumption behaviors, focusing on large scale enterprises that consume large amount of energy resources such as electricity, gas, and water. It has developed advanced wireless gateways and data aggregators to directly measure and collect the energy consumption data in real-time, particularly for industrial factories. Once the large amount of wireless energy measurement sensors are deployed in a factory, how to form an optimized mesh network to bring all sensor nodes together and read the meters in an efficient way poses a significant challenge. This Engage project seeks to tackle the challenges through algorithm design and system integration. A multi-disciplinary team involving Dr. Liu, SFU graduate students and software engineers from Rimeware will be assembled. We will analyze the sensor and network settings from Rimeware's application environment, and the structure of the data generated from the sensors. We will then implement the algorithms for data collection over distributed sensors and data processing on cloud platforms, and test using the data supplied by Rimeware. The outcome will be integrated into Rimeware's data collection and processing platform, and the performance will be evaluated with realworld sensor and network configurations.