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- Title
- OPEN SOURCE BUILDING SCIENCE SENSORS (OSBSS) : A LOW-COST ARDUINO-BASED PLATFORM FOR LONG-TERM DATA COLLECTION IN INDOOR ENVIRONMENTS
- Creator
- Ali, Akram Syed
- Date
- 2015, 2015-05
- Description
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Accurate characterization of building characteristics that influence indoor air quality (IAQ), thermal comfort, and energy consumption in...
Show moreAccurate characterization of building characteristics that influence indoor air quality (IAQ), thermal comfort, and energy consumption in buildings is often limited to the use of proprietary hardware and software, which can adversely affect both functionality and costs. In response, the Open Source Building Science Sensors (OSBSS) project was launched to design and develop a network of inexpensive open source devices based on the Arduino platform for measuring and recording long-term indoor environmental and building operational data. The project includes a variety of sensors and dataloggers designed to assess energy, comfort, and air quality in buildings, including air and surface temperatures, air relative humidity, surface water activity, human occupancy and activity, light intensity, CO2, and a generic datalogger that can log data from other sensors such as HVAC system pressure sensors for determining system airflow rates or runtimes. The development, calibration, and performance of the sensor network is being documented in its entirety and made available freely online along with detailed tutorials designed to allow other researchers to incorporate the sensors in both ongoing and future investigations of energy, air quality, and comfort in the built environment. The OSBSS network of devices will ultimately allow for more flexibility in synchronizing a large number of measurements with high spatial and temporal resolution in a more cost effective manner for use in research projects and building automation and control.
M.S. in Civil, Architectural and Environmental Engineering, May 2015
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- Title
- ADVANCING OPEN-SOURCE TOOLS FOR INDOOR ENVIRONMENTAL MONITORING AND BUILDING SYSTEMS CONTROLS USING WIRELESS SENSOR NETWORKS
- Creator
- Ali, Akram Syed
- Date
- 2021
- Description
-
Incorporating data monitoring and visualization tools in buildings can provide a glimpse into their energy use, thermal performance, daily...
Show moreIncorporating data monitoring and visualization tools in buildings can provide a glimpse into their energy use, thermal performance, daily operation, and maintenance requirements. However, buildings have traditionally been monitored using hardware and software that are expensive, proprietary, and often limited in terms of ease of use and flexibility. Many existing buildings remain unmonitored or poorly monitored, leaving many opportunities for energy savings and improving indoor environmental conditions unaddressed. To this end, the goal of this research is to develop and demonstrate an open-source hardware and software platform for monitoring and controlling the performance of buildings and their systems, called Elemental. It is designed to provide real-time data on indoor environmental quality, energy usage, heating, ventilating, and air-conditioning (HVAC) operation, and other factors to its users, and provide easy development of building controls. It combines: (i) custom low power printed circuit boards (PCBs) with RF transceivers for wireless sensors, control nodes, and USB gateway, (ii) a Raspberry Pi with custom firmware acting as a backhaul, and (iii) custom software applications that manage data storage, device configuration and interface for querying and visualizing the data in real-time. The platform is built around the idea of a private, secure, and open technology for the built environment. Among its many applications, the platform allows occupants to investigate anomalies in energy usage, environmental quality, and thermal performance. It also includes multiple frontends to view and analyze building activity data, which can be used directly in building controls. This proposal describes the development process of the hardware and software used in the Elemental platform along with three distinct applications including: (1) deployment in a research lab for long-term data collection and automated analysis, (2) use as a full-home energy and environmental monitoring solution, and (3) building heating system automation at the room-level with the development and deployment of a custom radiator control. Through these applications, this work demonstrates that the platform allows easy and virtually unlimited datalogging, monitoring, and analysis of real-time sensor data with low setup costs. Low-power sensor nodes placed in abundance in a building can also provide precise and immediate fault-detection, allowing for tuning equipment for more efficient operation and faster maintenance during the lifetime of the building.
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