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. The continual advancement in semiconductor technology has enabled vendors to integrate an increasing number of sensors, e.g., accelerometer, gyroscope, digital compass, high resolution cameras and others, in modern mobile phones. Combining with the ever expanding market penetration of mobile phones, the onboard sensors are driving the sensing community towards a new paradigm called participatory sensing in which ordinary citizens voluntarily collect and share information from their local environment using personal mobile devices. The inherent openness of this platform is a double-edged sword. While encouraging user participation on the one hand, it also makes it easy to contribute corrupted data. As such, data trustworthiness becomes a key issue which needs to be addressed to ensure sustainable development of this emerging paradigm. In this paper, we propose a reputation system in which a reputation score is calculated for each device as a reflection of the trustworthiness of its sensor data. We adopt the Gompertz function as a fundamental building block of our system, since it is better suited to deal with the unique characteristics of participatory sensing. We present an application-agnostic implementation of the system, which can work with a wide variety of participatory sensing applications. We evaluate the performance of our reputation system in the context of two real-world participatory sensing applications. Our results show that the proposed reputation system outperforms existing solutions by up to a factor of six. This article presents P-Sense, a participatory sensing application for air pollution monitoring and control. The paper describes in detail the system architecture and individual components of a successfully implemented application. In addition, the paper points out several other research-oriented problems that need to be addressed before these applications can be effectively implemented in practice, in a large-scale deployment. Security, privacy, data visualization and validation, and incentives are part of our work-in-progress activities Participatory sensing is emerging as an innovative computing paradigm that targets the ubiquity of always-connected mobile phones and their sensing capabilities. In this paper, a multitude of pioneering applications increasingly carry out pervasive collection and dissemination of information and environmental data, such as traffic conditions, pollution, temperature, and so on. Participants collect and report measurements from their mobile devices and entrust them to the cloud to be made available to applications and users. Naturally, due to the personal information associated to the reports (e.g., location, movements, etc.), a number of privacy concerns need to be considered prior to a large-scale deployment of these applications. Motivated by the need for privacy protection in participatory sensing, this paper presents a privacy-enhanced participatory sensing infrastructure. We explore realistic architectural assumptions and a minimal set of formal requirements aiming at protecting privacy of both data producers and consumers. We propose two instantiations that attain privacy guarantees with provable security at very low additional computational cost and almost no extra communication overhead. We present an ultra low-cost sensing system, which enables participants to see and reflect on the particulates in their air. Drawing on prior work in paper computing, we introduce small sensors for particulate pollution that can be easily assembled from common paper materials for less than $1 USD, and mailed by regular postal service to residents of entire neighborhoods, cities, or geographic regions. Recipients collect particulate samples using these sensors and mail them back to a central location, where the particles are viewed and analyzed via a microscope. The data, which includes rich images of actual air pollution particles, can then be broadcast to larger audiences. This paper details the design of our system and its deployment with a local air quality activist community. We conclude by highlighting the tradeoffs between high-tech and low-tech sensing, and suggest opportunities for tangible interaction to support rich, new ways of seeing our environment. Mobile phones have evolved from devices that are just used for voice and text communication to platforms that are able to capture and transmit a range of data types (image, audio, and location). The adoption of these increasingly capable devices by society has enabled a potentially pervasive sensing paradigm - participatory sensing. A coordinated participatory sensing system engages individuals carrying mobile phones to explore phenomena of interest using in situ data collection. For participatory sensing to succeed, several technical challenges need to be solved. In this paper, we discuss one particular issue: developing a recruitment framework to enable organizers to identify well-suited participants for data collections based on geographic and temporal availability as well as participation habits. This recruitment system is evaluated through a series of pilot data collections where volunteers explored sustainable processes on a university campus. Grassroots Participatory Sensing empowers people to collect and share sensor data using mobile devices across many applications, spanning intelligent transportation, air quality monitoring and social networking. In this paper, we argue that the very openness of such a system makes it vulnerable to abuse by malicious users who may poison the information, collude to fabricate information, or launch Sybils to distort that information. We propose and implement a novel trusted platform module (TPM), or angel based system that addresses the problem of providing sensor data integrity. The key idea is to provide a trusted platform within each sensor device to attest the integrity of sensor readings. We argue that this localizes integrity checking to the device, rather than relying on corroboration, making the system not only simpler, but also resistant to collusion and data poisoning. A "burned-in" private key in the TPM prevents users from launching Sybils. We also make the case for content protection and access control mechanisms that enable users to publish sensor data streams to selected groups of people and address it using broadcast encryption techniques.