2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)最新文献

{"title":"A Novel Strategy under Charger Capture Attack in Wireless Rechargeable Sensor Networks","authors":"Nan Yu, Xiaoyu Wang, Haipeng Dai, Guihai Chen","doi":"10.1109/DCOSS49796.2020.00063","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00063","url":null,"abstract":"In this paper, we consider the problem of designing a novel ATTack scheme under charger cApture attaCK(ATTACK) in wireless rechargeable sensor networks. That is, there are a number of wireless chargers with directional antenna and rechargeable directional devices deployed in the 2D plane. An intelligent adversary selects a limited number of chargers to be captured and adjust the compromised chargers’ power factor such that the overall attacking utility of devices is maximized. To solve our ATTACK problem, we investigate an attacking algorithm with a constant approximation ratio with lightweight timing complexity. We conduct simulation experiments to verify the performance of our proposed attacking algorithm. The results shows that our proposed attacking algorithm can outperform the comparison algorithm by 69.95%.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121654990","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}

{"title":"Target Tracking using Radar and Image IoT Nodes","authors":"Pavlos Tsiantis, Sanil Ahan Purryag, I. Kyriakides","doi":"10.1109/DCOSS49796.2020.00072","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00072","url":null,"abstract":"The availability of multiple sensing and edge processing capabilities by sensing nodes, that may include radar, image, and acoustic, enables the collection of rich information to improve performance in target tracking. However, the tracking system, that includes a central data fusion center and IoT nodes, needs to extract information from heterogeneous data under constraints of IoT power, processing, and communication rates. This work presents a method for target tracking using image and radar data. The method is able to fuse heterogeneous data and direct agile edge processing of data on board of the sensing IoT nodes. Data fusion and agile edge processing improves tracking performance while reducing processing and communication rates. Simulation-based results, using synthetic radar data and real image data, demonstrate an improved tracking performance when using heterogeneous data versus using a single type of data.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125985180","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}

{"title":"Towards Human-Aware D2D Communication","authors":"R. Costa, A. C. Viana, A. Ziviani, L. Sampaio","doi":"10.1109/DCOSS49796.2020.00038","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00038","url":null,"abstract":"Mobility, social interactions, and other human characteristics shall support Future Mobile Networks in routine prediction and resource management. This work investigates human-aware metrics supporting services or protocols leveraging opportunistic communication. These metrics represent different types of knowledge extracted from people routine present in their movements. Because of the strong routine component of human mobility, such metrics capture different but recurrent behaviors on wireless encounters between mobile users. We report the experience through a case study with a real-world dataset along with results from trace and metrics analysis. The results show heterogeneity in metric coefficients and contact occurrence and duration in different periods of the day, highlighting the need for characterising traces before their use.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121536592","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}

{"title":"Atlas: Exploration and Mapping with a Sparse Swarm of Networked IoT Robots","authors":"Razanne Abu-Aisheh, F. Bronzino, M. Rifai, Brian G. Kilberg, K. Pister, T. Watteyne","doi":"10.1109/DCOSS49796.2020.00060","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00060","url":null,"abstract":"Exploration and mapping is a fundamental capability of a swarm of robots: robots enter an unknown area, explore it, and collectively build a map of it. This capability is important regardless of whether the robots are crawling, flying, or swimming. Existing exploration and mapping algorithms tend to either be inefficient, or rely on having a dense swarm of robots. This paper introduces Atlas, an exploration and mapping algorithm for sparse swarms of robots, which completes a full exploration even in the extreme case of a single robot. We develop an open-source simulator and show that Atlas outperforms the state-of-the-art in terms of exploration speed and completeness of the resulting map.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116652292","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}

{"title":"A Gesture Recognition approach to classifying Allergic Rhinitis gestures using Wrist-worn Devices : a multidisciplinary case study","authors":"X. Aggelides, Andreas Bardoutsos, S. Nikoletseas, Nikos Papadopoulos, C. Raptopoulos, Pantelis Tzamalis","doi":"10.1109/DCOSS49796.2020.00015","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00015","url":null,"abstract":"In this paper, we propose a multidisciplinary Gesture Recognition case study using a Machine Learning approach for the detection and classification of allergic rhinitis-related gestures. Allergic diseases and especially allergic rhinitis are among the most common diseases in the world, mostly underappreciated, causing considerable impairment of daily activities, including job, and school productivity. For this reason, close monitoring and early recognition of symptoms worsening are considered essential. We hypothesize that recognizing allergic rhinitis to patients by such an approach may be a useful tool for such purpose.In our study, for the first time, the most common allergic rhinitis gestures are identified, based on patients’ description and specialists’ experience. Our data is retrieved by a large pool of active allergic rhinitis patients attending three specialized outpatient clinics in Greece. Gestures are recorded with the help of a wristband Bluetooth device incorporating a 3-axis accelerometer and a 3-axis gyroscope. Feature engineering and several signal processing methods are then applied to the raw sensor data (which are treated as 6-dimensional signals), and valuable features are extracted related to the time and frequency domains.To improve the performance of the Machine Learning models, we utilize Principal Component Analysis (PCA), and we also use functions such as Grid Search and Randomized Search, in order to achieve higher recognition accuracy by hyperparameter optimization.With these features and steps of processing, we built a classifier that can uniquely identify 15 allergic rhinitis gestures with an accuracy of 93% in a challenging variety of moves in the patient’s head (nose, eye, ear). It is worth noting that allergic rhinitis gestures are more subtle, varied and spontaneous than other moves that have been considered in the literature so far. To the best of our knowledge, this is the first time that a Machine Learning approach is successfully applied in such a challenging field like respiratory diseases.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117210297","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}

{"title":"An Automatic Platform for Landing and Charging of UAVs to Extend UAV Operations","authors":"Anthony Aboumrad, J. Haun, Alexander McGinnis, Nansong Wu","doi":"10.1109/DCOSS49796.2020.00061","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00061","url":null,"abstract":"With the increasing popularity of unmanned aerial vehicle (UAV), especially electric quadcopters used in commercial deployment, there is a demand for a solution that allows for automatic landing and recharging of UAVs as needed to extend the operation range. In this paper, we propose a novel system design that can automatically land and wireless charge of the UAV. We design a computer vision based landing guidance system enclosed in a charging platform, and a charging attachment for universal fit on a UAV. We demonstrate the design by building a landing and charging platform and testing it with a UAV. Our system achieves accurate landings and successfully recharging of the UAV battery. We share our source code online to foster further developments in assisted landing and wireless charging in UAV communities.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122694627","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}

{"title":"DCOSS 2020 TOC","authors":"J. Stankovic, S. Nirjon","doi":"10.1109/dcoss49796.2020.00004","DOIUrl":"https://doi.org/10.1109/dcoss49796.2020.00004","url":null,"abstract":"Foreword to DCOSS 2020 xiv DCOSS 2020 Organizing Committee xv DCOSS 2020 Steering Committee xvi DCOSS 2020 Technical Program Committee xvii Message from the UrbCom 2020 Workshop Chairs xviii Message from the IoTI4 2020 Workshop Chairs xix Message from the Wi-DroIT 2020 Workshop Chairs xx Message from the WPSN 2020 Workshop General Chair xxii Message from the ISIoT 2020 Workshop Chairs xxiii Message from the Joint Workshop on Emerging Topics in Sensor Systems Chairs xxiv","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116253884","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}

{"title":"Concurrent Wireless Cut-Through Forwarding: Ultra-Low Latency Multi-Hop Communication for the Internet of Things","authors":"Nicolás Himmelmann, Dingwen Yuan, Lars Almon, M. Hollick","doi":"10.1109/DCOSS49796.2020.00024","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00024","url":null,"abstract":"Achieving low latency remains a challenge in today’s industrial Internet of Things (IoT) applications, particularly if operated over wireless multi-hop networks. One idea that can distinctly reduce the multi-hop latency is the so-called cut-through forwarding, i.e., a node starts relaying a packet after it has only received a fraction of it by leveraging two radios. This paper proposes the novel concurrent wireless cut-through (CWCT) protocol based on a prototype design which combines two off-the- shelf IoT devices. To improve reliability and eliminate routing overhead, CWCT applies concurrent transmission and Golay error correction coding. Evaluation on a controlled topology and on a medium-size testbed shows the large reduction in latency of CWCT compared to Glossy and the high synchronicity of concurrent transmission. To further improve packet reliability, we need to reduce the out-of-band leakage.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125596991","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}

{"title":"MicaPen: A Pen to Write in Air Using Mica Motes","authors":"Amitangshu Pal","doi":"10.1109/DCOSS49796.2020.00035","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00035","url":null,"abstract":"This paper demonstrates a technique to write in air using Micaz motes. The application, named MicaPen is low-cost and can be used by the disabled who does not have fingers or limbs. Patients can wear the mote as a wrist watch or bracelet and move their hands based on what character they want to write. The mote detects the movement pattern using the accelerometer of MTS310 sensorboard and displays the characters on the screen. The application can also be extended in several applications including virtual touchscreen or remotely interact with different controlled devices.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"82 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123237912","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}

{"title":"Accurate Deep Net Crowd Counting for Smart IoT Video acquisition devices","authors":"Anish R. Khadka, V. Argyriou, Paolo Remagnino","doi":"10.1109/DCOSS49796.2020.00049","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00049","url":null,"abstract":"A novel deep neural network is proposed, for accurate and robust crowd counting. Crowd counting is a complex task, as it strongly depends on the deployed camera characteristics and, above all, the scene perspective. Crowd counting is essential in security applications where Internet of Things (IoT) cameras are deployed to help with crowd management tasks. The complexity of a scene varies greatly, and a medium to large scale security system based on IoT cameras must cater for changes in perspective and how people appear from different vantage points. To address this, our deep architecture extracts multi-scale features with a pyramid contextual module to provide long-range contextual information and enlarge the receptive field. Experiments were run on three major crowd counting datasets, to test our proposed method. Results demonstrate our method supersedes the performance of state-of-the-art methods.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123255773","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}