NoxDroid A Bicycle Sensor System for Air Pollution Monitoring

Transcription

1 NoxDroid A Bicycle Sensor System for Air Pollution Monitoring Andreas Bok Andersen aboa@itu.dk Pelle Krøgholt pelle@itu.dk Stine Bierre sbie@itu.dk Aurélien Tabard auta@itu.dk pitlab IT University Copenhagen Rued Langgaards Vej 7, DK 2300 Copenhagen S Abstract We present NoxDroid a sensor system aimed at monitoring air quality in cities. We designed NoxDroid to address health and environmental concerns both at a personal and societal level. NoxDroid is a small mobile sensor device built and mounted on bicycles by volunteers. The sensor provides low fidelity real-time feedback on air quality and connects to an Android application for more advanced functionalities. For example, NoxDroid users can upload air quality information to a web server to visualize it on a map or process it in their own way. Our preliminary evaluation with 3 participants highlighted some directions for improving our current implementation, such as battery life or its physical form factor. Keywords Sensor, pollution, bicycle, monitoring, nox, air, mobile. sustainability, crowd sourcing Copyright is held by the author/owner(s). CHI 2012, May 5 10, 2012, Austin, TX, USA. ACM xxx-x-xxxx-xxxx-x/xx/xx. ACM Classification Keywords H.5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous. I.2.9 Robotics: Sensors. General Terms Design.

2 2 Figure 1. NoxDroid mounted on bicycles Handlebars. Introduction Air quality is an important concern in capitals of developed and emerging countries. These concerns cover both health and environment problems which has led international authorities and organizations to issue Guidelines and Directives on air and pollution 0. In order to act in an informed manner, several national research initiatives are investigating the actual distribution of air pollution. Many of these initiatives rely on stationary monitors measuring a variety of compounds very precisely for scientific purposes. Such is the case of Denmark s primary research project on air quality, led by the Danske Miljøundersøgelser (DMU)[2,3]. However, the data collected by these stations is neither provided nor accessible to the general public, thus leaving citizens blind in respect to air quality in their surroundings. To mitigate these limitations, several research projects investigated both crowd sourcing sensing (to have more sensing points as well as mobile ones), and presenting the resulting information to citizens. However most of these solutions do not provide direct feedback for the carrier or manager of the sensor nodes 0. This lack of direct feedback is a problem if volunteers have to mount and spend time on using the devices. Not getting relevant information might decrease the chances of adoption and result in less motivated participants. In order to get a quality dataset, it seems necessary to provide users with information they can draw direct benefits from and gain a feeling that it makes sense to sense. Related Work The Copenhagen Wheel [7] is the most relevant example of a mobile, bicycle-based, sensing system. The design proposed by the MIT Senseable city labs is based on an augmented wheel, collecting data on the level of NOx, CO and noise while harnessing energy from the breakers. An iphone application connects via Bluetooth to the Wheel, gathers location data, uploads sensor data to a web server and visualizes the gathered information, providing real-time and post-hoc feedback. In the last couple of years the production of mobile sensors has accelerated and researchers experimented with different sensor types, devices, systems architectture and networking [1,6,8,9]. Tsow et al. [8] proposed to use Bluetooth connection between a mobile device and a sensor device identifying VOCs (unhealthy aromatic compounds). The system is based on a very cheap, wearable tuning fork sensor, built into a cell phone sized hard case, and a cell phone. As with the Copenhagen Wheel the Bluetooth connection poses many technical problems as most Bluetooth units consume a lot of energy when doing constant polling, which has led phone manufacturers to force disconnection after 120 or 180 seconds. As an alternative, Al-Ali et al. 0 proposed having a sensor device directly posting its data to a Pollution Server using a GPRS modem. In their case, the sensor measures NO 2, CO and SO 2 and packs them in frames with GPS coordinates, time and date. The Pollution- Server stores the data and uses Google Maps to visualize pollution levels the user is (and has been) exposed to. Tudose et al. [9] measured NOx, SOx and CO, which are all strongly correlated with car exhaust. By measuring these compounds and mapping them, the

3 3 public authorities might in the long run make initiatives that can minimize the environmental problem caused by cars. Sensing device An important design consideration for NoxDroid was to keep it accessible and cheap (below $100). In comparison the Copenhagen Wheel has an estimated price of $600, which has made critics call it too clever for its own good [5]. We built the sensor device out of old-fashioned BASTA bicycle light (seen to the left on this page). Such lights can be found in second hands shops for a very cheap price or even for free. The device consists of an air sensor (MQ-135 Air Quality Control Sensor), which measures NOx, NH3, alcohol, benzene, smoke and CO2 ($7). The sensor is controlled by an IOIO board for Android1 ($50) and powered by a 9V battery. The IOIO also controls 3 LEDs of different colors visible in fig 2.C. The LEDS provide live feedback on the air quality (green being good, yellow concerning and red bad). To succeed in distributing sensor systems to the everyday user of the city, the system must be designed so that users can directly benefit from it. Sensing and visualizing the air pollution in a lot of the related works are based on a sensor/mobile device and a remote database, which means that users do not have direct access to the sensor information while moving around the city. To distribute sensors to the population individuals have to realize the problem and see direct benefits, before spending time on learning the system. In other words it needs to make sense to sense. Therefore the system has to be simple, robust and cheap enough while providing direct feedback to the user. NoxDroid The system can be self-made with common tools, a soldering kit and a guide available online with the code2. Moreover any do it yourself (DIY) amateur can put the different pieces together. We designed NoxDroid to provide individuals with tools to understand the quality of the air they breathe daily. To provide a balance between simplicity and accuracy, we focused on NOx particles, which are good indicator for the presence of other unhealthy and polluting compounds [3]. Figure 2. Sensing device: A. Casing B. Air sensor C. Feedback LEDs Android Application The NoxDroid Android application is in charge of the connection to the IOIO board, saving sensor data GPS locations and uploading the collected data to a web service at Google App Engine. It also controls the LEDS providing direct feedback on the NoxDroid device. NoxDroid is a mobile sensing device that can be attached to the handlebar of bicycles and which works in conjunction with an Android phone (see fig. 1). The sensing device (fig. 2) provides instant feedback on the air quality, while the Android part collects sensor data, combine it to location data and uploads it to a web application for later use. For GPS tracking, two background services listen and save location changes broadcast by SKYHOOK and the phone s built-in location service. To improve power

4 4 consumption we use a fixed update interval with giving a max time (8s) between location reports for SKYHOOK. The built-in location service is set up to use network, cell towers and GPS. Optimizing update interval and location change, currently set to minimum values, to balance granularity and system load is subject to further refinements. We built (and tested) the application to be compatible with Android SDK level 8 (Android 2.2) and up. For that reason the NoxDroid Android application can be used on a very wide range of Android supported phones from low to high-end phones. We have specifically tested the application both on a low level phone like the Huawei U8150 Ideos (costs approximately $100) and a highend phone like Samsung Galaxy S. Figure 4. Screenshot of NoxDroid app with connection to GPS and Wifi but no connection to the IOIO board. From the users perspective, the NoxDroid application (figure 4) shows if it is properly connected to GPS, Wifi and the sensor box. It allows users to start and stop recording data and upload it once a trip is finished. Figure 3. NoxDrop setup: A sensor device connected to an Android application. Web application Users can also visit noxdroid.org webpage to have an overview of the pollution they were exposed to. After entering their ID, they can see their routes on a map-

5 5 based interface (figure 5). The visualization comprises a search tool where single and multiple tracks can be viewed as data overlays on a map. Users can restrict the search to their NoxDroid-id while non-users view anonymized data. The website also includes blog posts with reflections and discussion of technical aspects. with sensor data and can serve data for other services as well. This API is implemented through simple HTTP GET/POST requests. Data processing and KML To visualize the data overlay we map the recorded NOx readings and GPS locations. As the sensor readings are done independently we insert GPS points on a straight line between consecutive pairs of GPS locations to geotag each intermediate NOx reading. Thus line segments on the overlay show the level of the NOx as green, yellow and red. The data can also be downloaded as KML and loaded on any map visualization tool such as Google Earth. Preliminary testing and feedback Figure 5. Screenshot of the NoxDroid pollution map. We are using the Google App Engine3 as a cloud based storage for the sensor recordings from the users of the system. We use the low-level object oriented data store of the App Engine based upon the high replication storage designed to scale well. We also use the App Engine to serve the visualization website, noxdroid.org 3 We tested NoxDroid with three participants riding their bicycle: Sara, 29 years old biking 10km everyday and generally concerned about her health; Stine, 27 years old biking 5km everyday in the inner city, is concerned about pollution when is seems to directly affect her (e.g. standing behind a truck exhaust); Frederik a 30 years old father biking 7km in less congested areas and concerned about his and his child s health but not about the pollution in general. From this summary only Sara and Stine seemed interested in using a sensor device. The tests also highlighted the need for better energy management of the phone and sensors, which had their battery drained quickly. The form factor of NoxDroid received mixed feedback, to some the DIY nature and retro look felt engaging while too cheap to others. Finally to better handle set-up and battery life a physical on/off button on the sensor device is necessary.

6 6 While the minimal live visualization was well received, more advanced visualization are necessary both at a personal level, but also aggregating more intelligently the readings from participants. We are investigating the different types of visualization (e.g. with average data per district or more fined grained quantitative information) with the aim to balance the richness of the information conveyed and its accuracy Conclusion We presented the NoxDroid mobile sensor system for air quality. We designed NoxDroid to be replicable in a DIY fashion and financially accessible. The project is in progress and we are planning on improving battery life, the setup process and the web application with personal and social features. Finally we are exploring the wide array of existing sensors to see how NoxDroid could become a more generic platform gathering a variety of environmental data such as VOC, noise or electromagnetic field strength. Acknowledgements Blank for review Citations [1] A.R. Al-Ali, I, Zualkerman and F. Aloul (2010). A Mobile GPRS-Sensors Array for Air Pollution Monitoring. IEEE SENSORS JOURNAL, VOL 10 NO 10, pp [2] DMU, NO2 and NO: Tendenser for årsmiddelværdier, Retrieved from DMU, Danmarks Miljøundersøgelser, Aarhus Universitet. [3] DMU, Oversigtsside om kvælstofoxider: NO, NO2, NOx, Retrieved from DMU, Danmarks Miljøundersøgelser, Aarhus Universitet. [4] Directive 2008/50/EC of the European Parliament and of the Council on ambient air quality and cleaner air for Europe. [5] GreenLivingBlog, 2010, Retrieved from the Guardian: [6] A. Steed and R. Milton (2008). Using tracked mobile sensors to make maps of environmental effects. Personal Ubiquitous Comput. 12, 4. [7] C. Outram, C. Ratti, and A. Biderman. (2010). The Copenhagen Wheel: An innovative electric bicycle system that harnesses the power of real-time information and crowd sourcing.ecologic Vehicles Renewable Energies, 1-8. [8] F. Tsow, E. Forzani, A. Rai, R. Wang, R. Tsui, S. Mastroianni, C. Knobbe, A. J. Gandolfi and N.J. Tao. (2009). A Wearable and Wireless Sensor System for Real-Time Monitoring of Toxic Environmental Volatile Organic Compounds, IEEE SENSORS JOURNAL, VOL 9 NO 12, pp [9] D. Ş. Tudose, T. A. Pătraşcu, A. Voinescu, R. Tătăroiu and N. Ţăpuş. (2011). Mobile sensors in air pollution measurement. CORD Conference Proceedings, pp [10] G. Vuk and C. Overgaard Hansen. (2010). Modellering af cykeltransportadfærd. TRAFIK & VEJE, pp [11] WHO Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide, Global update 2005, Summary of risk assessment, World health Organisation, Geneva 2006.