HomeReACT a Tool for Real-time Indoor Environmental Monitoring

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1 HomeReACT a Tool for Real-time Indoor Environmental Monitoring Tessa Daniel, Elena Gaura, James Brusey Cogent Computing Applied Research Centre Faculty of Engineering and Computing Coventry University, Priory Street, Coventry, UK CV1 5FB [email protected] [email protected] [email protected] No Institute Given Abstract. Wireless indoor environmental monitoring (WIEM) systems are becoming an important tool in the fight to reduce carbon emissions and improve energy efficiency in the built environment. Systems which previously targeted the commercial market are quickly moving into the residential domain with promises of drastic energy reduction. The requirements of a WIEM system, however, vary from application to application and the information generated and presented depends on the needs of the relevant stakeholders. The research showcased here seeks to develop a dynamically reconfigurable WIEM system that is multiapplication and multi-stakeholder focused. HomeReACT incorporates an off-the-shelf wireless mesh network and operates in 3 application modes: event-centric mode allows for the detection and isolation of threshold events, data-centric mode allows for retrieval of current and historical data using parameter-based queries and information-centric mode allows the user to monitor high level, easy to understand information about the deployment. An early system prototype has been used in a number of residential and commercial deployments and will be demonstrated in each of the three modes. 1 Motivation In the fight against climate change, improving energy efficiency in both residential and commercial buildings is the focus of a number of energy conservation initiatives at a governmental level [1,2]. Building monitoring is a fast growing application area for wireless sensor networks (WSNs) and a number of commercial systems are marketed as the solution to the energy problem [3,4,5,6]. These applications are limited, however, in that they do not cater for varying requirements within different application contexts; they do not take into account the different informational needs of the various stakeholders and, they do not cater for easy-to-understand representation of the information to the stakeholder. WIEM applications may have different requirements, for example, sensor modality, required data sampling rate for fast or slow changing phenomena

Wireless indoor environmental monitoring (WIEM) systems are becoming an important tool in the fight to reduce carbon emissions and improve energy efficiency in the built environment.

2 and data aggregation. When the data/information is provided may also be important, for example, real-time as opposed to offline. In commercial systems, real-time functionality is generally limited to alarms triggered when parameter thresholds are exceeded at a sensing point. Furthermore, many systems are inflexible and do not allow for system reconfiguration, on the fly, to suit a range of applications needs. The information generated should also depend on the needs of the stakeholder. A house occupant, for example, is not interested in time series parameter measurements but wants to know why a room is not comfortable whereas an emergency responder may need to locate and track an event, such as a fire, to be able to respond quickly. Presentation is also key to effectiveness and usability of the system. A colour coded comfort map of a room, for example, is easier to understand and has greater visual impact than a table of comfort index values. This research proposes the development of HomeReACT, a multi-mode WIEM system that seeks to address the issues raised above. The system is intended to be flexible enough to allow for the deployment of different types of applications while also catering for various stakeholders within the individual applications. Most important is the ability to change the modality of the system dynamically, at run time, without the need to reprogram or redeploy nodes. The system can be tasked in three modes: event-centric, data-centric and information-centric and has been used in a number of deployments. 2 System Description 2.1 Hardware The Arch Rock platform [3] is an off-the-shelf wireless sensor network system that facilitates the development of WSN applications. A basic deployable WSN system is composed of a server, a router, and sensor nodes. The server is a Linuxbased PC, able to communicate with the router over Ethernet and the router bridges the Ethernet network and an IPv based low power wireless mesh network (6LowPAN). Fig. 1. Server, router and 3G modem (left) and sensor node with integrated CO2 sensor (right).

Furthermore, many systems are inflexible and do not allow for system reconfiguration, on the fly, to suit a range of applications needs.

Each node contains a number of integrated sensors: a Sensirion SHT-11 sensor (temperature and humidity) a Hamamatsu S-1087 (photosynthetically active radiation light) a Hamamatsu S-1087-1 (total

3 Each node contains a number of integrated sensors: a Sensirion SHT-11 sensor (temperature and humidity) a Hamamatsu S-1087 (photosynthetically active radiation light) a Hamamatsu S (total solar radiation light). An Environment Leading Technology (ELT) B-530 CO2 sensor was also integrated in-house. Nodes contain packet radios and software that allow them to communicate using mesh routing protocols with the routers and other sensor nodes. Figure 1 shows the system hardware. 2.2 Software A web-based interface allows interaction with the system in each of its 3 modes (event-centric, data-centric and information-centric). Python-based modules and scripts run on the server tasking the network according to the selected mode. This also allows statistical analyses of historical data to be generated upon request. Periodic system health status information is transmitted via a 3G modem to a remote monitoring server, with a user-set log frequency (reprogrammable on the fly). The health status includes: the quantity of collected sensor data; and status of nodes, router and server. This modem can also be used to log into the server during troubleshooting. 3 The Demonstration The demonstrator will comprise a wireless sensor network (WSN) deployed to monitor temperature, humidity, CO2 and light. The HomeReACT application will run on the server with the user interface accessible via a laptop. The system will be demonstrated in 3 modes. 3.1 Event-centric Mode Fig.2. Event-centric mode: Map showing location of detected temperature event and the spatial boundary of the event (left) and sample deployment status log sent via 3G messaging system (right.)

Nodes contain packet radios and software that allow them to communicate using mesh routing protocols with the routers and other sensor nodes. Figure 1 shows the system hardware. 2.

4 Detecting Events In event-centric mode, the system will detect and isolate a threshold event. The temperature will be raised at some location within the deployment space, the application will identify and locate the event. As the event evolves over time a contour bounding the event will be drawn on an interpolated 2D map of the deployment area. Figure 2 shows a sample map of a detected event. Detecting Faults The web-based health monitoring logging system will also be demonstrated through the introduction and identification of a variety of network faults. Possible faults include: a node which has stopped gathering data, faulty sensor readings, and disconnected nodes. A sample log is shown in figure 2. Fig.3. Data-centric Mode: interpolated temperature map in a monitored room shown on left and results of a query for historical CO 2data shown on right. 3.2 Data-centric Mode In data-centric mode, the user will select a parameter (temperature, humidity, CO2) to monitor over the sensored space. The parameter s evolution over space and in real-time will be displayed using an interpolated map. A sample map is shown in figure 3. In addition, the historical data query page will be shown. The results of a query for CO 2 data are shown in figure Information-centric Mode Information-centric mode will highlight a number of possible methods for providing meaningful information to the user. A real-time comfort monitoring application that incorporates multi-sensor, multi-type data fusion will be demonstrated as well as time-compressed videos of slow changing phenomena within the deployment space.

As the event evolves over time a contour bounding the event will be drawn on an interpolated 2D map of the deployment area. Figure 2 shows a sample map of a detected event.

5 Fig.4. Information-centric mode: comfort maps of a monitored commercial space. 4 Concluding Remarks The application described here covers the motivating first steps towards developing a system that allows monitoring and evaluation of buildings in both the commercial and residential market. HomeReACT has high innovative value as it moves away from mono-functional WSN systems to create a multi-application, multi-user centred system that allows reconfiguration of the system while running. It allows acquisition and viewing of real-time data through user-defined queries, automated analyses of stored data and generates in real-time high level abstract information through data fusion, filtering and reduction. It also presents the monitoring results to the user using a number of informational representation methods. The hope is that the system can be used to provide useful information in moving towards a low-energy building solution. References [1] Department of Energy and Climate Change (n.d.) Home Energy Saving Programme [online] available from < [June ] [2] Department of Energy and Climate Change (n.d.) Smart Meters [online] available from < [June ] [3] Arch Rock (n.d.) Arch Rock Technology [online] available from < [June ] [4] SensiNode (n.d.) From innovation to integration [online] available from < [June ] [5] SpinWave (n.d.) Spinwave Solutions [online] available from < [June ] [6] MicroWatt (n.d.) Power Manager [online] availabe from < [June ]

Sensor network infrastructure for intelligent building monitoring and management system

Sensor network infrastructure for intelligent building monitoring and management system 1 R.VENKATESH, 2 K.RADHA, 3 M.GANTHIMATHI 1.B.E-CSE, Muthayammal Engineering College, Rasipuram. 2. Assistant Professor