Abstract
This work demonstrates an open-source hardware and software platform for monitoring the performance of buildings, called Elemental, that is designed to provide data on indoor environmental quality, energy usage, HVAC operation, and other factors to its users. It combines: (i) custom printed circuit boards (PCBs) with RFM69 frequency shift keying (FSK) radio frequency (RF) transceivers for wireless sensors, control nodes, and USB gateway, (ii) a Raspberry Pi 3B with custom firmware acting as either a centralized or distributed backhaul, and (iii) a custom dockerized application for the backend called Brood that serves as the director software managing message brokering via Message Queuing Telemetry Transport (MQTT) protocol using VerneMQ, database storage using InfluxDB, and data visualization using Grafana. 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 via a comprehensive dashboard with rich querying capabilities. It also includes multiple frontends to view and analyze building activity data, which can be used directly in building controls or to provide recommendations on how to increase operational efficiency or improve operating conditions. Here, we demonstrate three distinct applications of the Elemental platform, 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) fault and anomaly detection and diagnostics of individual building systems at the zone-level. Through these applications we demonstrate 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.
Highlights
Understanding the complex relationships between occupant activity, air quality, energy usage, and occupant comfort levels in buildings requires monitoring many subsystems in addition to the perceived comfort of occupants [1,2,3]
This paper proposes an open-source hardware and software platform, called the Elemental platform, that enables real-time and historical analysis of a building’s performance and thermal comfort of occupants within by: (1) integrating accurate, inexpensive, low power wireless sensors and controls; (2) connecting existing commercial Internet of Things (IoT) devices, heating, ventilation, and air-conditioning (HVAC)
To address thethe aforementioned issues with existing technologies, we we developed custom printed circuit boards (PCBs) measuring common indoor environmental building operational circuit boards (PCBs) for for measuring common indoor environmental andand building operational parameters, including surface temperature, relative humidity, light intensity, barometric parameters, including air air andand surface temperature, relative humidity, light intensity, barometric pressure, motionactivity, activity,carbon carbon dioxide matter, totaltotal volatile organic pressure, motion dioxide
Summary
Understanding the complex relationships between occupant activity, air quality, energy usage, and occupant comfort levels in buildings requires monitoring many subsystems in addition to the perceived comfort of occupants [1,2,3]. Sensors 2019, 19, 4017 energy use data is already available in many existing building energy management systems These systems typically do not utilize real-time activity data within buildings to inform their control strategies, nor do they make that data available for analysis, in smaller residential and commercial buildings for which building energy management systems are often prohibitively expensive [5]. This results in unsatisfactory thermal comfort for occupants, inefficient usage of energy (especially during unoccupied periods), and a lack of zone-level anomaly detection for buildings and systems
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