An Internet of Things Framework for Smart Energy in Buildings: Designs, Prototype, and Experiments

By Jianli Pan, Raj Jain, S. Paul, Tam N. Vu, Abusayeed Saifullah, M. Sha. IEEE Internet of Things Journal, 2015

336 citations recorded by the source corpus.

Smart energy in buildings is an important research area of Internet of Things (IoT). As important parts of the smart grids, the energy efficiency of buildings is vital for the environment and global sustainability. Using a LEED-gold-certificated green office building, we built a unique IoT experimental testbed for our energy efficiency and building intelligence research. We first monitor and collect 1-year-long building energy usage data and then systematically evaluate and analyze them. The results show that due to the centralized and static building controls, the actual running of green buildings may not be energy efficient even though they may be “green” by design. Inspired by “energy proportional computing” in modern computers, we propose an IoT framework with smart location-based automated and networked energy control, which uses smartphone platform and cloud-computing technologies to enable multiscale energy proportionality including building-, user-, and organizational-level energy proportionality. We further build a proof-of-concept IoT network and control system prototype and carried out real-world experiments, which demonstrate the effectiveness of the proposed solution. We envision that the broad application of the proposed solution has not only led to significant economic benefits in term of energy saving, improving home/office network intelligence, but also bought in a huge social implication in terms of global sustainability.

Subfields: Building and Construction, Electrical and Electronic Engineering, Media Technology

View Paper: https://www.semanticscholar.org/paper/6e0514d5d138eadda73ee42122fdb408a0def981

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Citations in the corpus

Software-Defined Networking for Internet of Things: A Survey (2017, background): “Typically, an IoT architecture consists of several sensor and RFID nodes forming large-scale distributed embedded systems for different real-time applications such as smart health-care [6], [7], intelligent transportation systems [8], and smart energy systems [9]–[11].”
Empowering Things With Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things (2020, background): “smart buildings [253], [255] can be regarded as the extension of smart grids AIoT (Section IV-F).”
The Internet of Things, Fog and Cloud Continuum: Integration and Challenges (2018, background): “On one hand there is a plethora of studies that argue for the benefits that IoT can bring in reducing energy consumption in various settings [58, 59, 60, 61].”
Internet of Things-Aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions (2017, methodology): “Its software includes a GPS location data recording software, and a configuration and management software for WiFi routers [154].”
Internet of Things for Green Building Management: Disruptive Innovations Through Low-Cost Sensor Technology and Artificial Intelligence (2018, background): “In this context, the IoT opens new opportunities to integrate intelligence into the BMS in a cost-effective manner through seamless integration of various sensors, smart meters, and actuators: the BMS can use these to monitor and identify different energy and environment-related parameters [3], anal”
Application of Big Data and Machine Learning in Smart Grid, and Associated Security Concerns: A Review (2019, background): “Connected vehicles, distributed energy resources (DER), green buildings are some more applications [35]–[37].”
A Survey of Machine Learning Techniques Applied to Software Defined Networking (SDN): Research Issues and Challenges (2019, background): “and smart energy systems [252]–[254], by leveraging largescale distributed embedded systems to connect billions of sensors and RFID nodes.”