Effective monitoring and management of environment pollution is key to the development of modern metropolitan cities. To sustain and to cope with the exponential growth of the cities with high industrialization, expert decision making is very essential in this process. A good governance system must be supported by an actively participating population. In participatory sensing, individuals and groups engages in the data collection actively and the helps the city governance to make proper decisions. In this paper, we propose a participatory sensing based three-tier framework to fight environment pollution in urban areas of Bangladesh. The framework includes an android application named My City, My Environment', a server for storage and computation and also a web server for the authority to monitor and maintain environmental issues through expert decision making. We have already developed a prototype system and deployed it to a small scale and demonstrated the effectiveness of this framework.
Environment pollution is an area where participatory sensing can play a lead role in data collection and management @cite_13 . Effective waste management in urban area is handled in @cite_32 @cite_30 . The air quality control or monitoring applications often comes with low cost sensors interfaced with mobile phones or devices. Such examples are Gas-Mobile @cite_2 , Common Sense @cite_14 and P-sense @cite_12 . An air temperature monitoring system was proposed in @cite_16 that collects air temperature from the temperature of the mobile phone batteries. A successful application of crowd-sourcing and participatory sensing in water monitoring in World Water monitoring challenge http: www.monitorwater.org . It includes 1458517 participants from 142 countries in the world reporting 70,927 water bodies @cite_5 . Creek Watch @cite_8 uses iPhone application to employ users to aid water management. Iphone camera is also used in reporting water quality in @cite_9 .
@cite_30 @cite_14 @cite_8 @cite_9 @cite_32 @cite_2 @cite_5 @cite_16 @cite_13 @cite_12
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Our work explores the convergence between participatory sensing, political activism and public expressions. Unlike prior research, which focuses on personal sensing, we present low-cost, networked air quality sensors, designed to be repositioned across public landscapes by communities of citizen stakeholders. Our GPS-enabled sensors report dust, exhaust, or VOC's (volatile organic compounds), along with temperature, humidity and light levels to a website that visualizes this data in real time. The sensors can be attached to a variety of surfaces serving as research probes to demarcate ('tag') public spaces with environmental concerns. We deploy our fully functional system with four urban communities - parents, bicyclists, homeless and activists, positioning our system as a tool for studying and supporting community togetherness and public activism. Our findings highlight community sharing of the physical sensors and dialogues surrounding the collected data. Because participatory sensing – targeted campaigns where people harness mobile phones as tools for data collection – involves large and distributed groups of people, participatory sensing systems benefit from tools to measure and evaluate the contributions of individual participants. This paper develops a set of metrics to help participatory sensing organizers determine individual participants’ fit with any given sensing project, and describes experiments evaluating the resulting reputation system. I. INTRODUCTION The rapid adoption of mobile phones over the last decade and an increasing ability to capture, classify, and transmit a wide variety of data (image, audio, and location) have enabled a new sensing paradigm – participatory urban sensing – where humans carrying mobile phones act as, and contribute to, sensing systems [1], [2], [3]. In this paper, we discuss an important factor in participatory sensing systems: measurement and evaluation of participation and performance during sensing projects. In participatory sensing, mobile phone-based data gathering is coordinated across a potentially large number of participants over wide spans of space and time. We draw from three pilot projects to illustrate participatory sensing and describe the unique challenges to measurement and evaluation provided by “campaigns”: distributed and targeted efforts to collect data. Project Budburst [4], Personal Environmental Impact Report (PEIR) [5], and Walkability all situate “humans in the loop”, but have critical differences in their goals and challenges (Table I). The recent wave of sensor-rich, Internet-enabled, smart mobile devices such as the Apple iPhone has opened the door for a novel paradigm for monitoring the urban landscape known as participatory sensing. Using this paradigm, ordinary citizens can collect multi-modal data streams from the surrounding environment using their mobile devices and share the same using existing communication infrastructure (e.g., 3G service or WiFi access points). The data contributed from multiple participants can be combined to build a spatiotemporal view of the phenomenon of interest and also to extract important community statistics. Given the ubiquity of mobile phones and the high density of people in metropolitan areas, participatory sensing can achieve an unprecedented level of coverage in both space and time for observing events of interest in urban spaces. Several exciting participatory sensing applications have emerged in recent years. For example, GPS traces uploaded by drivers and passengers can be used to generate realtime traffic statistics. Similarly, street-level audio samples collected by pedestrians can be aggregated to create a citywide noise map. In this talk, we will provide a comprehensive overview of this new and exciting paradigm and outline the major research challenges. Participatory sensing is a revolutionary new paradigm in which volunteers collect and share information from their local environment using mobile phones. The inherent openness of this platform makes it easy to contribute corrupted data. This paper proposes a novel reputation system that employs the Gompertz function for computing device reputation score as a reflection of the trustworthiness of the contributed data. We implement this system in the context of a participatory noise monitoring application and conduct extensive real-world experiments using Apple iPhones. Experimental results demonstrate that our scheme achieves three-fold improvement in comparison with the state-of-the-art Beta reputation scheme.