Users who retrieve information across disadvantaged networks need to do so in such a way as to minimize network performance impact while maximizing the usefulness and quality of information (QOI) received. Taking advantage of features from all three network genres (telecommunication, information, and social) will enable this balancing act. These users also need to interact using unstructured, ad-hoc queries to decrease the cognitive overload of specialized training or the necessity of learning a constrained language. High QOI can be maintained if an intelligent agent on the network can use social sensing to capture the intent of the query and identify the implied task. Knowing the task will allow other agents that service the requests to filter, summarize, or transcode data prior to responding, lessening the network footprint. This paper describes an approach that uses natural language processing (NLP) techniques, multi-valued logic based inferencing, network status checking, and task-relevant metrics for information retrieval. This research effort has resulted in a low-level NLP approach that can be used to capture intent from unstructured text, a quality metric formed from intrinsic and extrinsic attributes of the objects and the tasks under consideration, and a simple inferencing approach to allow intelligent agents to make quality assessments, delivering the appropriate form of the information that will lessen the impact on a disadvantaged network.
{"title":"Using Intelligent Agents for Social Sensing across Disadvantaged Networks","authors":"Reginald L. Hobbs, William Dron","doi":"10.1109/MASS.2015.96","DOIUrl":"https://doi.org/10.1109/MASS.2015.96","url":null,"abstract":"Users who retrieve information across disadvantaged networks need to do so in such a way as to minimize network performance impact while maximizing the usefulness and quality of information (QOI) received. Taking advantage of features from all three network genres (telecommunication, information, and social) will enable this balancing act. These users also need to interact using unstructured, ad-hoc queries to decrease the cognitive overload of specialized training or the necessity of learning a constrained language. High QOI can be maintained if an intelligent agent on the network can use social sensing to capture the intent of the query and identify the implied task. Knowing the task will allow other agents that service the requests to filter, summarize, or transcode data prior to responding, lessening the network footprint. This paper describes an approach that uses natural language processing (NLP) techniques, multi-valued logic based inferencing, network status checking, and task-relevant metrics for information retrieval. This research effort has resulted in a low-level NLP approach that can be used to capture intent from unstructured text, a quality metric formed from intrinsic and extrinsic attributes of the objects and the tasks under consideration, and a simple inferencing approach to allow intelligent agents to make quality assessments, delivering the appropriate form of the information that will lessen the impact on a disadvantaged network.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123567623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
People carry smartphones that have a variety of radios and sensors. Increasingly, smartphone applications use the radios and sensors to determine a user's location and to sense motion. Nevertheless, most existing smartphone applications cannot avoid accumulative errors when calculating position and movement. In this paper, we propose a novel approach, Air Loc - Adopting mobile robots to assist indoor Localization of smartphones. A moving robot employs a Bluetooth adapter and a known map to assist a smartphone to reduce its localization error. When a robot is near a smartphone, the robot sends accurate location information to users' smartphones via Bluetooth. We design a path planning strategy for a robot to enhance the localization accuracies of smartphones over extended time periods. Moreover, in order to promote the single robot approach, we extend it to the multi-robot assisted indoor localization. The multi-robots are organized by an unbalanced tree and serve areas by the Distance/Density First Algorithm. Through experimentation and simulation in a multi-room building, we evaluate Air Loc and believe it is promising as a cost-efficient means to yield average positioning error below 0.9 meter and possibly lead to better localization results for some scenarios, including shopping mall and hospital.
人们携带的智能手机有各种各样的无线电和传感器。越来越多的智能手机应用程序使用无线电和传感器来确定用户的位置和感知运动。然而，大多数现有的智能手机应用程序在计算位置和运动时无法避免累积误差。在本文中，我们提出了一种新颖的方法，Air Loc -采用移动机器人来辅助智能手机的室内定位。移动机器人使用蓝牙适配器和已知地图来帮助智能手机减少定位错误。当机器人靠近智能手机时，机器人会通过蓝牙向用户的智能手机发送准确的位置信息。为了提高智能手机在长时间内的定位精度，我们设计了一种机器人路径规划策略。此外，为了推广单机器人方法，我们将其扩展到多机器人辅助的室内定位。多机器人由非平衡树组织，采用距离/密度优先算法服务区域。通过在多房间建筑中的实验和模拟，我们评估了Air Loc，并相信它是一种具有成本效益的方法，可以产生低于0.9米的平均定位误差，并可能在一些场景中获得更好的定位结果，包括购物中心和医院。
{"title":"AirLoc: Mobile Robots Assisted Indoor Localization","authors":"Chen Qiu, M. Mutka","doi":"10.1109/MASS.2015.10","DOIUrl":"https://doi.org/10.1109/MASS.2015.10","url":null,"abstract":"People carry smartphones that have a variety of radios and sensors. Increasingly, smartphone applications use the radios and sensors to determine a user's location and to sense motion. Nevertheless, most existing smartphone applications cannot avoid accumulative errors when calculating position and movement. In this paper, we propose a novel approach, Air Loc - Adopting mobile robots to assist indoor Localization of smartphones. A moving robot employs a Bluetooth adapter and a known map to assist a smartphone to reduce its localization error. When a robot is near a smartphone, the robot sends accurate location information to users' smartphones via Bluetooth. We design a path planning strategy for a robot to enhance the localization accuracies of smartphones over extended time periods. Moreover, in order to promote the single robot approach, we extend it to the multi-robot assisted indoor localization. The multi-robots are organized by an unbalanced tree and serve areas by the Distance/Density First Algorithm. Through experimentation and simulation in a multi-room building, we evaluate Air Loc and believe it is promising as a cost-efficient means to yield average positioning error below 0.9 meter and possibly lead to better localization results for some scenarios, including shopping mall and hospital.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121141105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Weiping Zhu, Yi-Cheng Hong, V. Raychoudhury, Run Zhao, Dong Wang
In recent decades, a growing number of large-scale RFID systems are used in various applications. In such a system, it is not uncommon that multiple concurrent radio communications among RFID readers and tags cause serious inference (called collision in the RFID field). One important kind of method to achieve collision-free communication is to activate RFID readers in different time slots. Existing activation approaches for solving this problem are mainly centralized, which is impractical due to the lack of central server, one-point failure risk, and performance bottleneck. Some distributed algorithms are proposed recently, but failed to consider the adaptiveness of the identification, where all of the RFID readers need to participate in the coordination control even if they do not have communication requirements any more. As a result, the optimal identification performance cannot be achieved. In this paper, we propose an adaptive distributed reader activation approach called ADRA for large-scale RFID systems. We build a fine-grained conflict graph for different kinds of collisions. And then a shared permission based distributed approach is adopted to eliminate those collisions. We guarantee that the RFID readers that do not need to communicate any more are suspended and excluded from the execution of coordination eventually. Extensive simulation results show that our approach outperforms existing approaches in terms of execution time and message overhead.
{"title":"Adaptive Distributed Reader Activation Approach for Large-Scale RFID Systems","authors":"Weiping Zhu, Yi-Cheng Hong, V. Raychoudhury, Run Zhao, Dong Wang","doi":"10.1109/MASS.2015.11","DOIUrl":"https://doi.org/10.1109/MASS.2015.11","url":null,"abstract":"In recent decades, a growing number of large-scale RFID systems are used in various applications. In such a system, it is not uncommon that multiple concurrent radio communications among RFID readers and tags cause serious inference (called collision in the RFID field). One important kind of method to achieve collision-free communication is to activate RFID readers in different time slots. Existing activation approaches for solving this problem are mainly centralized, which is impractical due to the lack of central server, one-point failure risk, and performance bottleneck. Some distributed algorithms are proposed recently, but failed to consider the adaptiveness of the identification, where all of the RFID readers need to participate in the coordination control even if they do not have communication requirements any more. As a result, the optimal identification performance cannot be achieved. In this paper, we propose an adaptive distributed reader activation approach called ADRA for large-scale RFID systems. We build a fine-grained conflict graph for different kinds of collisions. And then a shared permission based distributed approach is adopted to eliminate those collisions. We guarantee that the RFID readers that do not need to communicate any more are suspended and excluded from the execution of coordination eventually. Extensive simulation results show that our approach outperforms existing approaches in terms of execution time and message overhead.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130621594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a new principled framework for exploiting time-sensitive information to improve the truth discovery accuracy in social sensing applications. This work is motivated by the emergence of social sensing as a new paradigm of collecting observations about the physical environment from humans or devices on their behalf. These observations maybe true or false, and hence are viewed as binary claims. A fundamental problem in social sensing applications lies in ascertaining the correctness of claims and the reliability of data sources. We refer to this problem as truth discovery. In this paper, we develop a new time-sensitive truth discovery scheme that explicitly incorporates the source responsiveness and the claim lifespan into a rigorous analytical framework. The preliminary results showed that our new scheme outperforms all compared baselines and significantly improves the truth discovery accuracy in social sensing applications.
{"title":"Time-Aware Truth Discovery in Social Sensing","authors":"Chao Huang, Dong Wang","doi":"10.1109/MASS.2015.50","DOIUrl":"https://doi.org/10.1109/MASS.2015.50","url":null,"abstract":"This paper presents a new principled framework for exploiting time-sensitive information to improve the truth discovery accuracy in social sensing applications. This work is motivated by the emergence of social sensing as a new paradigm of collecting observations about the physical environment from humans or devices on their behalf. These observations maybe true or false, and hence are viewed as binary claims. A fundamental problem in social sensing applications lies in ascertaining the correctness of claims and the reliability of data sources. We refer to this problem as truth discovery. In this paper, we develop a new time-sensitive truth discovery scheme that explicitly incorporates the source responsiveness and the claim lifespan into a rigorous analytical framework. The preliminary results showed that our new scheme outperforms all compared baselines and significantly improves the truth discovery accuracy in social sensing applications.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132209084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigated several smartphone-based applications designed for citizens to record encounters with law enforcement officers. The study aimed to analyze the different applications based on their initialization speed, ease of recording, upload speed and robustness. The study also sought to provide the developers of future applications with insight into what attributes are most important to this type of applications. We found that in general, applications of this kind do not always function consistently. The design features that proved the most beneficial were uploading in a broadcast style, providing ample information regarding the status of an upload, and saving a local copies of videos recorded in the app.
{"title":"Survey of Smartphone-Based Police Monitoring Apps","authors":"Amy Puente, C. C. Tan","doi":"10.1109/MASS.2015.27","DOIUrl":"https://doi.org/10.1109/MASS.2015.27","url":null,"abstract":"This study investigated several smartphone-based applications designed for citizens to record encounters with law enforcement officers. The study aimed to analyze the different applications based on their initialization speed, ease of recording, upload speed and robustness. The study also sought to provide the developers of future applications with insight into what attributes are most important to this type of applications. We found that in general, applications of this kind do not always function consistently. The design features that proved the most beneficial were uploading in a broadcast style, providing ample information regarding the status of an upload, and saving a local copies of videos recorded in the app.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133924001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we propose a novel geographic routing protocol, called Greedy Routing Protocol with Backtracking (GRB), for Mobile Ad Hoc Networks, which uses a simple backtracking technique to deal with voids. Performance evaluation shows GRB has much less routing overhead than that of AODV as well as GPSR. It has higher packet-delivery ratio, lower end-to-end delay, and less hop count on average than AODV.
{"title":"GRB: Greedy Routing Protocol with Backtracking for Mobile Ad-Hoc Networks","authors":"Baban A. Mahmood, D. Manivannan","doi":"10.1109/MASS.2015.49","DOIUrl":"https://doi.org/10.1109/MASS.2015.49","url":null,"abstract":"In this paper, we propose a novel geographic routing protocol, called Greedy Routing Protocol with Backtracking (GRB), for Mobile Ad Hoc Networks, which uses a simple backtracking technique to deal with voids. Performance evaluation shows GRB has much less routing overhead than that of AODV as well as GPSR. It has higher packet-delivery ratio, lower end-to-end delay, and less hop count on average than AODV.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134334633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the rapid development of mobile applications, there is an urgent need for highly efficient indoor localization service. Dedicated systems achieve good accuracy at the cost of deploying special hardware. Fingerprint-based methods avoid maintaining the expensive infrastructure but suffer from intensive labor for site-survey and poor robustness. In this paper, we present Per Loc, an infrastructure-free localization system which leverages rich vision features in indoor environment with high efficiency and accuracy. Per Loc makes use of binocular ranging technique to calculate the depth of a feature point and then figures out its geographical coordinates to build up reference point database, for which we design a filtering scheme to keep the database efficient in storage and search delay. During the localization stage, users simply take a photo of surroundings and feature points are extracted automatically as input for search scheme. Then a fast two-stage search scheme is proposed to find the nearest neighbors of query feature points in reference point database. Based on the perspective projection model, we inversely calculate users' geographical location in real time. We implement the proposed localization system on commercial smartphones as well as laptops and conduct extensive experiments. Per Loc achieves 1.76m of average error in office environment, and 2.2m of average error in shopping mall.
{"title":"PerLoc: Enabling Infrastructure-Free Indoor Localization with Perspective Projection","authors":"Puchun Feng, Lan Zhang, Kebin Liu, Yunhao Liu","doi":"10.1109/MASS.2015.47","DOIUrl":"https://doi.org/10.1109/MASS.2015.47","url":null,"abstract":"With the rapid development of mobile applications, there is an urgent need for highly efficient indoor localization service. Dedicated systems achieve good accuracy at the cost of deploying special hardware. Fingerprint-based methods avoid maintaining the expensive infrastructure but suffer from intensive labor for site-survey and poor robustness. In this paper, we present Per Loc, an infrastructure-free localization system which leverages rich vision features in indoor environment with high efficiency and accuracy. Per Loc makes use of binocular ranging technique to calculate the depth of a feature point and then figures out its geographical coordinates to build up reference point database, for which we design a filtering scheme to keep the database efficient in storage and search delay. During the localization stage, users simply take a photo of surroundings and feature points are extracted automatically as input for search scheme. Then a fast two-stage search scheme is proposed to find the nearest neighbors of query feature points in reference point database. Based on the perspective projection model, we inversely calculate users' geographical location in real time. We implement the proposed localization system on commercial smartphones as well as laptops and conduct extensive experiments. Per Loc achieves 1.76m of average error in office environment, and 2.2m of average error in shopping mall.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133397246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Warwick, Nicholas Symons, Xiao Chen, Kaiqi Xiong
The National Highway Traffic Safety Administration data show that drowsy driving causes more than 100,000 crashes a year. In order to prevent these devastating accidents, it is necessary to build a reliable driver drowsiness detection system which could alert the driver before a mishap happens. In the literature, the drowsiness of a driver can be measured by vehicle-based, behavior-based, and physiology-based approaches. Comparing with the vehicle-based and behavior-based measurements, the physiological measurement of drowsiness is more accurate. With the latest release of wireless wearable devices such as biosensors that can measure people's physiological data, we aim to explore the possibility of designing a user-friendly and accurate driver drowsiness detection system using wireless wearables. In this paper, we use a wearable biosensor called Bio Harness 3 produced by Zephyr Technology to measure a driver's physiological data. We present our overall design idea of the driver drowsiness detection system and the preliminary experimental results using the biosensor. The detection system will be designed in two phases: The main task of the first phase is to collect a driver's physiological data by the biosensor and analyze the measured data to find the key parameters related to the drowsiness. In the second phase, we will design a drowsiness detection algorithm and develop a mobile app to alert drowsy drivers. The results from this project can lead to the development of real products which can save many lives and avoid many accidents on the road. Furthermore, our results can be widely applied to any situation where people should not fall asleep: from the applications in mission-critical fields to the applications in everyday life.
{"title":"Detecting Driver Drowsiness Using Wireless Wearables","authors":"B. Warwick, Nicholas Symons, Xiao Chen, Kaiqi Xiong","doi":"10.1109/MASS.2015.22","DOIUrl":"https://doi.org/10.1109/MASS.2015.22","url":null,"abstract":"The National Highway Traffic Safety Administration data show that drowsy driving causes more than 100,000 crashes a year. In order to prevent these devastating accidents, it is necessary to build a reliable driver drowsiness detection system which could alert the driver before a mishap happens. In the literature, the drowsiness of a driver can be measured by vehicle-based, behavior-based, and physiology-based approaches. Comparing with the vehicle-based and behavior-based measurements, the physiological measurement of drowsiness is more accurate. With the latest release of wireless wearable devices such as biosensors that can measure people's physiological data, we aim to explore the possibility of designing a user-friendly and accurate driver drowsiness detection system using wireless wearables. In this paper, we use a wearable biosensor called Bio Harness 3 produced by Zephyr Technology to measure a driver's physiological data. We present our overall design idea of the driver drowsiness detection system and the preliminary experimental results using the biosensor. The detection system will be designed in two phases: The main task of the first phase is to collect a driver's physiological data by the biosensor and analyze the measured data to find the key parameters related to the drowsiness. In the second phase, we will design a drowsiness detection algorithm and develop a mobile app to alert drowsy drivers. The results from this project can lead to the development of real products which can save many lives and avoid many accidents on the road. Furthermore, our results can be widely applied to any situation where people should not fall asleep: from the applications in mission-critical fields to the applications in everyday life.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132935423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vehicular ad hoc networks, as a special case of delay tolerant networks, have become increasingly attractive to academia and industry. Different from most of the work in this field, which has focused on short periods of transient opportunistic contacts, in our previous work, we have analyzed the position data of a large set of urban private vehicles in Changsha, China and proposed a Location based Urban Vehicular network (LUV) utilizing the stable connections among vehicles. Place serves as a central message exchange and routing component in LUV that is critical in providing relatively reliable network connections. In this paper, we present a simple threshold based approach for identifying the places or vehicle aggregation areas, in an urban environment. We perform experimental study over a real set of data gathered over three months for 8900 vehicles and show the method is effective.
{"title":"Place Identification in Location Based Urban VANETs","authors":"Heng Li, Yonghe Liu, Yi Sun, Ruiyun Yu","doi":"10.1109/MASS.2015.106","DOIUrl":"https://doi.org/10.1109/MASS.2015.106","url":null,"abstract":"Vehicular ad hoc networks, as a special case of delay tolerant networks, have become increasingly attractive to academia and industry. Different from most of the work in this field, which has focused on short periods of transient opportunistic contacts, in our previous work, we have analyzed the position data of a large set of urban private vehicles in Changsha, China and proposed a Location based Urban Vehicular network (LUV) utilizing the stable connections among vehicles. Place serves as a central message exchange and routing component in LUV that is critical in providing relatively reliable network connections. In this paper, we present a simple threshold based approach for identifying the places or vehicle aggregation areas, in an urban environment. We perform experimental study over a real set of data gathered over three months for 8900 vehicles and show the method is effective.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115332617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper develops a new principled framework for exploiting time-sensitive information to improve the truth discovery accuracy in social sensing applications. This work is motivated by the emergence of social sensing as a new paradigm of collecting observations about the physical environment from humans or devices on their behalf. These observations maybe true or false, and hence are viewed as binary claims. A fundamental problem in social sensing applications lies in ascertaining the correctness of claims and the reliability of data sources. We refer to this problem as truth discovery. Time is a critical dimension that needs to be carefully exploited in the truth discovery solutions. In this paper, we develop a new time-sensitive truth discovery scheme that explicitly incorporates the source responsiveness and the claim lifespan into a rigorous analytical framework. The new truth discovery scheme solves a maximum likelihood estimation problem to determine both the claim correctness and the source reliability. We compare our time-sensitive scheme with the state-of-the-art baselines through an extensive simulation study and a real world case study. The evaluation results showed that our new scheme outperforms all compared baselines and significantly improves the truth discovery accuracy in social sensing applications.
{"title":"Towards Time-Sensitive Truth Discovery in Social Sensing Applications","authors":"Chao Huang, Dong Wang, N. Chawla","doi":"10.1109/MASS.2015.39","DOIUrl":"https://doi.org/10.1109/MASS.2015.39","url":null,"abstract":"This paper develops a new principled framework for exploiting time-sensitive information to improve the truth discovery accuracy in social sensing applications. This work is motivated by the emergence of social sensing as a new paradigm of collecting observations about the physical environment from humans or devices on their behalf. These observations maybe true or false, and hence are viewed as binary claims. A fundamental problem in social sensing applications lies in ascertaining the correctness of claims and the reliability of data sources. We refer to this problem as truth discovery. Time is a critical dimension that needs to be carefully exploited in the truth discovery solutions. In this paper, we develop a new time-sensitive truth discovery scheme that explicitly incorporates the source responsiveness and the claim lifespan into a rigorous analytical framework. The new truth discovery scheme solves a maximum likelihood estimation problem to determine both the claim correctness and the source reliability. We compare our time-sensitive scheme with the state-of-the-art baselines through an extensive simulation study and a real world case study. The evaluation results showed that our new scheme outperforms all compared baselines and significantly improves the truth discovery accuracy in social sensing applications.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"60 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124320032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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