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Title: Hamilton: Flexible, Open Source $10 Wireless Sensor System for Energy Efficient Building Operation

Technical Report ·
DOI:https://doi.org/10.2172/1798959· OSTI ID:1798959
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  1. True, Inc. (United States)
  2. Univ. of California, Berkeley, CA (United States)
  3. Seoul National Univ. (Korea, Republic of)
  4. Colorado School of Mines, Golden, CO (United States)
  5. NASA Ames Research Center (ARC), Moffett Field, Mountain View, CA (United States)

Sensors for improving building performance are rapidly populating the market, driven in part by the drive to reduce greenhouse gas emissions resulting from energy production as well as improve the interior environment for healthy and more productive spaces. UC Berkeley has led wireless sensor development over the past 25 years (e.g., Telos mote), with the Hamilton (named after Alexander Hamilton on the US $10 bill) as the most recent. The Hamilton sensor was designed as a low-cost high-performance sensor that is modular and interoperable. The objective of the Hamilton project was to create, evaluate and establish the technological foundations for secure and easy to deploy building energy efficiency applications utilizing pervasive, low-cost wireless sensors integrated with traditional Building Management Systems (BMS), consumer-sector building components, and powerful data analytics. The project included iterative hardware design, incorporating a high-performance database (BTrDb, http://btrdb.io/), creating and iterating the development of secure data middleware (BOSSwave, WAVE/WAVEMQ), working with and pushing the development of an open-source tiny operating system RiotOS, and implementing and improving protocols such as Thread/OpenThread and TCP/IP. The hardware benefited from careful design to drive down the cost; the design included a System-on-a-Chip (SoC), chip antenna, single crystal and five passive components. Careful design of the operating system created a low-power design to enable a long life with small batteries. The hardware included several sensors: temperature, radiant temperature, relative humidity, magnetometer, accelerometer, and light, with an optional occupancy (Passive InfraRed) sensor. The project was the basis of several applications, both internal to the research team and other researchers and professionals at other institutions. Several applications used the sensor hardware as the basis for other complex devices. Other applications used the sensors to improve building performance through interoperating with the building Heating Ventilation and Air-Conditioning (HVAC) system, such as using occupancy and/or distributed temperature sensing to reduce HVAC zone energy while still providing thermal comfort and to reduce peak loads in small commercial buildings. We demonstrated cloud-based energy analytics, implemented a schedule and a Model Predictive Controller in a small commercial building to optimize HVAC energy, occupancy and electricity price. Initial integration of these technological innovations was performed through the creation of execution containers containing the WAVE agent and various driver, proxy, or building system function logic. The research added to the understanding of efficient sensor hardware, secure middleware, time-series data management (high performance database), efficient communication protocols, and interoperating with applications and building systems. The project showed the technical effectiveness and economic feasibility of creating a low-cost, modular, and easy-to-deploy sensor. Through conversations with multiple end users, the research team discovered that many customers wanted data management and services in addition to the sensors. HamiltonIOT developed packages of sensors, border router, and data services to provide a seamless “plug-and-play” sensor deployment. Some customers were willing to pay for higher quality sensors (such as light); some customers wanted a robust enclosure (waterproof).

Research Organization:
Univ. of California, Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office
DOE Contract Number:
EE0007685
OSTI ID:
1798959
Report Number(s):
DOE-UCB-7685
Country of Publication:
United States
Language:
English

References (10)

Thread/OpenThread: A Compromise in Low-Power Wireless Multihop Network Architecture for the Internet of Things journal July 2019
Challenging the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL): A Survey journal January 2017
Mortar: an open testbed for portable building analytics
  • Fierro, Gabe; Pritoni, Marco; AbdelBaky, Moustafa
  • BuildSys '18: The 5th ACM International Conference on Systems for Built Environments, Proceedings of the 5th Conference on Systems for Built Environments https://doi.org/10.1145/3276774.3276796
conference November 2018
Design and Analysis of a Query Processor for Brick journal December 2018
HodDB: a query processor for brick
  • Fierro, Gabe; Culler, David E.
  • BuildSys '17: The 4th ACM International Conference on Systems for Energy-Efficient Built Environments, Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments https://doi.org/10.1145/3137133.3141449
conference November 2017
Bringing Full-Scale TCP to Low-Power Networks
  • Kumar, Sam; Andersen, Michael P.; Kim, Hyung-Sin
  • SenSys '18: The 16th ACM Conference on Embedded Networked Sensor Systems, Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems https://doi.org/10.1145/3274783.3275196
conference November 2018
Hamilton: a cost-effective, low power networked sensor for indoor environment monitoring
  • Andersen, Michael P.; Kim, Hyung-Sin; Culler, David E.
  • BuildSys '17: The 4th ACM International Conference on Systems for Energy-Efficient Built Environments, Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments https://doi.org/10.1145/3137133.3141453
conference November 2017
System Architecture Directions for Post-SoC/32-bit Networked Sensors
  • Kim, Hyung-Sin; Andersen, Michael P.; Chen, Kaifei
  • SenSys '18: The 16th ACM Conference on Embedded Networked Sensor Systems, Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems https://doi.org/10.1145/3274783.3274839
conference November 2018
Dataset: An Open Dataset and Collection Tool for BMS Point Labels conference January 2019
Do Not Lose Bandwidth: Adaptive Transmission Power and Multihop Topology Control conference June 2017