{"content":"Current Project AirBox: A Participatory Sensing Ecosystem for PM2.5 Monitoring (https://pm25.lass-net.org)\nKeywords: PM2.5, Participatory Sensing, Smart City, Open Data\nAirBox Dataset: [download]\nObjective My research interests lie in the area of networked sensing systems and applications. The primary objectives of my research are 1) to investigate theoretical models of real world systems; 2) to conduct real world deployment to verify theoretical models; and 3) to combine theoretical models and system deployment to solve real world problems.\nSpecifically, we investigate participatory sensing systems that combine networked sensing and crowdsourcing techniques to collect streams of data of the surroundings at personal, society, and urban levels. We have carried out a comfort measuring system, called TPE-CMS, for public transportation systems in the greater Taipei area. Moreover, we have conducted data-driven research to discover knowledge and information from the collected data, and the results demonstrate that such system is feasible and scalable in yielding detailed information of transportation service and traffic conditions at the city level.\nIn addition, we research Internet of Things systems and develop a large-scale system, called AirBox, for PM2.5 monitoring system. The project engages citizens to participate in environmental sensing and enables them to make low-cost PM2.5 sensing devices on their own. It also facilitates PM2.5 monitoring at a finer spatio-temporal granularity and enriches environmental data analysis by making all measurement data freely available to everyone. Till 2020/9, we have deployed more than 15,000 devices in 58 countries, and we have developed a set of algorithms for device ranking, emission source detection, and anomaly detection. Based on our research results, we have been collaborating with the government agencies on smart governance, smart inspection, and the related issues.\nMy ongoing research focuses on spatio-temporal data analysis of IoT systems and its applications. We intend to apply our research results to other real-world networked sensing systems, such as participatory sensing for urban profiling, environmental monitoring, and wearable sensing and computing. Moreover, we wish to employ advanced artificial intelligence techniques to increase the smartness of networked sensing systems, and we will incorporate our research results with emerging social computing systems as a whole to facilitate cyber-physical socially networked systems in the future.\nPast Projects Bus+: A Comfort Measuring System for Public Bus Systems (http://cms.vprobe.org/)\nYushanNet: A Delay-Tolerant Sensor Network for Hiker Tracking, Search, and Rescuing in Yushan National Parks (http://nslab.ee.ntu.edu.tw/~YuShanNet/)\nCapProbe: (http://www.cs.ucla.edu/~nrl/CapProbe/)\n","items":[{"content":"We provide the sample dataset of the AirBox project (https://pm25.lass-net.org/). The project was inspired by the work of the Location Aware Sensing System (LASS) community, which engages citizens to participate in the PM2.5 sensing project and enables them to make low-cost PM2.5 sensing devices on their own. It also facilitates PM2.5 monitoring at a finer spatio-temporal granularity and enriches environmental data analysis by making all measurement data freely available to everyone. Till 2017/08, there have been more than 3,500 AirBox devices deployed in 30 countries worldwide.\nDescription Each sample dataset is a CSV (or zipped CSV) file that contains measurements of timestamp, GPS coordinates, temperature, relative humidity, PM1, PM2.5, and PM10 of AirBox devices in Taiwan in the given period. The detailed hardware information is below:\nDevice: Edimax AirBox AI-1001W V1 and V2 Temperature/Humidity sensor: HTS221 PM1/2.5/10 sensor: Plantower PMS5003 Sample rate: every 5-6 minutes Note that, some AirBox devices are using the old version firmware that does not provide PM1/PM10 measurement results. Moreover, due to different reasons, disconnection and reconnection are frequent in the dataset, and missing data is common for all the AirBox devices.\nDownload Note that this dataset is released for research institutes and non-profit organizations only. If you are from industry or plan to use this dataset for commercial purposes, you are NOT eligible to download this dataset, and please go to this page for more detailed information.\nJanuary 2017, Taiwan: [.csv] [.tgz] February 2017, Taiwan: [.csv] [.tgz] March 2017, Taiwan: [.csv] [.tgz] If you are interested in accessing real-time AirBox data, please refer to the \u0026ldquo;API\u0026rdquo; session on the PM2.5 Open Data Portal website.\nHow to cite this dataset? Please explicitly acknowledge the data source, Edimax Inc., when presenting the dataset (and any outcomes based on this dataset) in any formats. When writing papers that use AirBox dataset, we would highly appreciate if you could cite the dataset by adding this citation to your papers: Ling-Jyh Chen, Yao-Hua Ho, Hu-Cheng Lee, Hsuan-Cho Wu, Hao-Min Liu, Hsin-Hung Hsieh, Yu-Te Huang, and Shih-Chun Candice Lung. An Open Framework for Participatory PM2.5 Monitoring in Smart Cities. IEEE Access Journal, volume 5, pp. 14441-14454, July, 2017. The paper is also available for open access and download at http://dx.doi.org/10.1109/ACCESS.2017.2723919 Acknowledgement We wish to thank the Edimax Inc., the LASS community and Academia Sinica for their support, technical advice and administrative assistance. This research was supported in part by the Ministry of Science and Technology of Taiwan and Academia Sinica under Grants: MOST 105-2221-E-001-016-MY3, MOST 105-3011-F-001-002, MOST 106-3114-E-001-004 and AS-104-SS-A02.\n","lastmod":"2026-04-09T12:53:27+08:00","section":"research","summary":"We provide the sample dataset of the AirBox project (https://pm25.lass-net.org/). The project was inspired by the work of the Location Aware Sensing System (LASS) community, which engages citizens to participate in the PM2.5 sensing project and enables them to make low-cost PM2.5 sensing devices on their own. It also facilitates PM2.5 monitoring at a finer spatio-temporal granularity and enriches environmental data analysis by making all measurement data freely available to everyone. Till 2017/08, there have been more than 3,500 AirBox devices deployed in 30 countries worldwide.\n","tags":[],"title":"AirBox Dataset","url":"https://cclljj.github.io/research/airbox_dataset/"}],"lastmod":"2026-04-09T12:09:45+08:00","section":"research","summary":"Current Project AirBox: A Participatory Sensing Ecosystem for PM2.5 Monitoring (https://pm25.lass-net.org)\nKeywords: PM2.5, Participatory Sensing, Smart City, Open Data\nAirBox Dataset: [download]\nObjective My research interests lie in the area of networked sensing systems and applications. The primary objectives of my research are 1) to investigate theoretical models of real world systems; 2) to conduct real world deployment to verify theoretical models; and 3) to combine theoretical models and system deployment to solve real world problems.\n","tags":[],"title":"Research","url":"https://cclljj.github.io/research/"}