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检索条件"任意字段=18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022"

共 79 条记录，以下是11-20 订阅

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Publishing Asynchronous Event Times with Pufferfish Privacy 18

Publishing Asynchronous Event Times with Pufferfish Privacy

引用

18th annual international conference on distributed computing in sensor systems (dcoss)

作者： Ding, Jiaxin Ghosh, Abhirup Sarkar, Rik Gao, Jie Shanghai Jiao Tong Univ Shanghai Peoples R China Univ Cambridge Cambridge England Univ Edinburgh Edinburgh Midlothian Scotland Rutgers State Univ New Brunswick NJ USA

ISBN: (纸本)9781665495127

Publishing data from IoT devices raises concerns of leaking sensitive information. In this paper we consider the scenario of publishing data on events with timestamps. We formulate three privacy issues, namely, whether one can tell if an event happened or not;whether one can nail down the timestamp of an event within a given time interval;and whether one can infer the relative order of any two nearby events. We show that perturbation of event timestamps or adding fake events following carefully chosen distributions can address these privacy concerns. We present a rigorous study of privately publishing discrete event timestamps with privacy guarantees under the Pufferfish privacy framework. We also conduct extensive experiments to evaluate utility of the modified time series with real world location checkin and app usage data. Our mechanisms preserve the statistical utility of event data which are suitable for aggregate queries.

关键词： Privacy Differential privacy Publishing Perturbation methods Time series analysis Nails sensor systems

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A Differential BCG sensor System for Long Term Health Monitoring Experiment on the ISS 18

A Differential BCG Sensor System for Long Term Health Monito...

引用

18th annual international conference on distributed computing in sensor systems (dcoss)

作者： Kulau, Ulf Rust, Jochen Szafranski, Daniel Drobczyk, Martin Albrecht, Urs-Vito Hamburg Univ Technol Smart Sensors Hamburg Germany DSI Aerosp Technol GmbH Bremen Germany TU Braunschweig Braunschweig Germany German Aerosp Ctr DLR Inst Space Syst Cologne Germany Bielefeld Univ Med Fac OWL Dept Digital Med Bielefeld Germany

ISBN: (纸本)9781665495127

Comprehensive health monitoring is highly relevant for the safety of manned spaced missions. Ballistocardiography (BCG) is a method for providing information of the heart physiology by measuring accelerations on the body surface that are caused by forwarded heart and blood movements in the vascular system. In order to provide a sensor system with a high signal quality, this paper presents differential BCG sensing at the system level for digital accelerometers and its integration into a sensing system. the system is part of a running experiment of the Cosmic Kiss mission on the international Space Station (ISS). Compared to single sensor solutions, the noise power scales down to about 50%, the Signal to Noise Ratio (SNR) is increased by a factor of 1.87 and the BCG signal variability especially improves for diastole area. Furthermore, by exploiting differential sensing techniques, both high reliability is achieved and common mode interference is mitigated, which is of high importance within the scope of space applications. Beside the presentation of the entire wireless sensor system including differential sensing approach, pre-processing unit and Ultra Wideband (UWB) communication module, results of the pre-flight tests show the performance of the system as well as the suitability for targeted mission.

关键词： sensor System Ballistocardiography Deifferential Sensing Accelerometers Health Monitoring Human Spaceflight

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Drone-based Optimal and Heuristic Orienteering Algorithms Towards Bug Detection in Orchards 18

Drone-based Optimal and Heuristic Orienteering Algorithms To...

引用

18th annual international conference on distributed computing in sensor systems (dcoss)

作者： Sorbelli, Francesco Betti Coro, Federico Das, Sajal K. Palazzetti, Lorenzo Pinotti, Cristina M. Univ Perugia Dept Comp Sci & Math Perugia Italy Missouri Univ Sci & Technol Dept Comp Sci Rolla MO 65409 USA Univ Florence Dept Comp Sci & Math Florence Italy

ISBN: (纸本)9781665495127

In this paper, we consider the problem of using a drone to collect information within orchards in order to detect bugs. An orchard can be modeled as an aisle-graph, which is a regular data structure formed by consecutive aisles where trees are arranged in a straight line. For monitoring the presence of bugs, a drone flies close to the trees and takes videos and/or pictures that will be analyzed offline. As the drone's energy is limited, only a subset of locations in the orchard can be visited with a fully charged battery. those places that are most likely to be infested should be selected to promptly detect the parasite. We study the budgeted constrained position selection problem in the orchard from an algorithmic point of view. We present the Single-drone Orienteering Aisle-graph Problem (SOAP), a variant of the well-known orienteering problem where the finite resource is the drone's battery. We first show that SOAP can be optimally solved for aisle-graphs in polynomial time. However, the optimal solution is not efficient for large orchards. then, we propose two efficient heuristics that work even for large (orchard) instances. After a thorough analysis of the proposed solutions, we evaluate their performance by simulation experiments on both synthetic and real data sets.

关键词： Heuristic algorithms Computer bugs Data models sensor systems Batteries Simple object access protocol distributed computing

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Efficient Localness Transformer for Smart sensor-Based Energy Disaggregation 18

Efficient Localness Transformer for Smart Sensor-Based Energ...

引用

18th annual international conference on distributed computing in sensor systems (dcoss)

作者： Yue, Zhenrui Zeng, Huimin Kou, Ziyi Shang, Lanyu Wang, Dong Univ Illinois Sch Informat Sci Champaign IL 61820 USA

ISBN: (纸本)9781665495127

Modern smart sensor-based energy management systems leverage non-intrusive load monitoring (NILM) to predict and optimize appliance load distribution in real-time. NILM, or energy disaggregation, refers to the decomposition of electricity usage conditioned on the aggregated power signals (i.e., smart sensor on the main channel). Based on real-time appliance power prediction using sensory technology, energy disaggregation has great potential to increase electricity efficiency and reduce energy expenditure. With the introduction of transformer models, NILM has achieved significant improvements in predicting device power readings. Nevertheless, transformers are less efficient due to O(l2) complexity w.r.t. sequence length l. Moreover, transformers can fail to capture local signal patterns in sequenceto-point settings due to the lack of inductive bias in local context. In this work, we propose an efficient localness transformer for non-intrusive load monitoring (ELTransformer). Specifically, we leverage normalization functions and switch the order of matrix multiplication to approximate self-attention and reduce computational complexity. Additionally, we introduce localness modeling with sparse local attention heads and relative position encodings to enhance the model capacity in extracting short-term local patterns. To the best of our knowledge, ELTransformer is the first NILM model that addresses computational complexity and localness modeling in NILM. With extensive experiments and quantitative analyses, we demonstrate the efficiency and effectiveness of the the proposed ELTransformer with considerable improvements compared to state-of-the-art baselines.

关键词： Smart sensor systems non-intrusive load monitoring energy disaggregation transformer

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Smart-Hop: Low-Latency Multi-hop Networking for LoRa 18

Smart-Hop: Low-Latency Multi-hop Networking for LoRa

引用

18th annual international conference on distributed computing in sensor systems (dcoss)

作者： Ahmar, Absar-Ul-Haque Joosen, Wouter Hughes, Danny Katholieke Univ Leuven Comp Sci Imec DistriNet Leuven Belgium

ISBN: (纸本)9781665495127

Low Power Wide Area Networks (LPWANs) provide the Internet of things (IoT) with energy-efficient, low cost, and long-range networking. LoRaWAN is one of the most widely deployed and studied LPWAN technologies due to its license-free operation and open standard, which has enabled 3rd parties to deploy millions of networks worldwide. LoRa allows transmission range and speed to be traded off by configuring the Spreading Factor (SF) setting. By tuning this parameter, the performance envelope of the network can be configured to favor a higher speed or longer range. While the SF of LoRA provides a simple and elegant means to tailor performance, at the highest spreading factor, maximum throughput drops to a few bits per second, dramatically increasing data extraction times. In this paper, we address this problem by proposing Smart-Hop, a novel multi-hop MAC layer protocol for LoRa which implements low-overhead routing. In contrast to prior work, Smart-Hop exploits the variable range afforded by different SFs to eliminate much of the complexity and overhead of traditional multi-hop mesh networking. Smart-Hop reduces the number of end-devices operating at high SFs while implementing low overhead routing in order to reduce data extraction times. these improvements are achieved while preserving the maximum range offered by LoRa in its highest SF configuration.

关键词： Low Power Wide Area Networks (LPWAN) LoRa Spreading Factor (SF) allocation Wireless sensor Networks (WSN) mesh networking.

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AI Powered COVID-19 Detection System using Non -Contact Sensing Technology and Deep Learning Techniques 18

AI Powered COVID-19 Detection System using Non -Contact Sens...

引用

18th annual international conference on distributed computing in sensor systems (dcoss)

作者： Kogilavani, S., V Sathishkumar, V. E. Subramanian, Malliga Kongu Engn Coll Dept Comp Sci & Engn Erode Tamil Nadu India Hanyang Univ Dept Ind Engn 222 Wangsimini Ro Seoul 04763 South Korea

ISBN: (纸本)9781665495127

the SARS-CoV-2 virus causes coronary artery disease (COVID-19). the majority of persons who are infected with the virus will have mild to severe respiratory illness and recover without the need for therapy. Some, on the other hand, will become critically unwell and require medical assistance. People over the age of 65, as well as those with underlying medical diseases such as cardiovascular disease, diabetes, chronic respiratory disease, or cancer, are at a higher risk of developing serious illness. Being thoroughly informed on the disease and how it spreads is the best strategy to avoid and slow down transmission. Stay at least 1 metre apart from other people to avoid infection. In this research work, we focus on how non-contact sensing technology and deep learning technique are being used to detect COVID-19 and assist healthcare workers in caring for COVID-19 patients. the proposed system captures images from the patient using non -contact sensing technologies and feeds the data into deep learning convolutional neural network architectures such as VGG16, VGG19, ResNet101, NASNet, DenseNet121, MobileNet, Xception, EfficientNet, and InceptionV3. In comparison to other architectures, the VGG16 architecture delivers superior accuracy.

关键词： Non-Contact sensor Deep Learning COVID-19 Health Care Respiratory System VGG16

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SynchroSim: An Integrated Co-simulation Middleware for Heterogeneous Multi-robot System 18

SynchroSim: An Integrated Co-simulation Middleware for Heter...

引用

18th annual international conference on distributed computing in sensor systems (dcoss)

作者： Dey, Emon Hossain, Jumman Roy, Nirmalya Busart, Carl Univ Maryland Baltimore Cty Ctr Real Time Distributed Sensing & Auton Dept Informat Syst Baltimore MD 21228 USA DEVCOM Army Res Lab Adelphi MD USA

ISBN: (纸本)9781665495127

With the advancement of modern robotics, autonomous agents are now capable of hosting sophisticated algorithms, which enables them to make intelligent decisions. But developing and testing such algorithms directly in real -world systems is tedious and may result in the wastage of valuable resources. Especially for heterogeneous multi -agent systems in battlefield environments where communication is critical in determining the system's behavior and usability. Due to the necessity of simulators of separate paradigms (co -simulation) to simulate such scenarios before deploying, synchronization between those simulators is vital. Existing works aimed at resolving this issue fall short of addressing diversity among deployed agents. In this work, we propose SynchroSim, an integrated co -simulation middleware to simulate a heterogeneous multi-robot system. Here we propose a velocity difference-driven adjustable window size approach with a view to reducing packet loss probability. It takes into account the respective velocities of deployed agents to calculate a suitable window size before transmitting data between them. We consider our algorithm specific simulator agnostic but for the sake of implementation results, we have used Gazebo as a Physics simulator and NS -3 as a network simulator. Also, we design our algorithm considering the Perception -Action loop inside a closed communication channel, which is one of the essential factors in a contested scenario with the requirement of high fidelity in terms of data transmission. We validate our approach empirically at both the simulation and system level for both line -of-sight (LOS) and non -line-of-sight (NLOS) scenarios. Our approach achieves a noticeable improvement in terms of reducing packet loss probability (approximate to 11%), and average packet delay (approximate to 10%) compared to the fixed window size-based synchronization approach.

关键词： Heterogeneous multi-robot systems NS-3 Gazebo Co-simulation Synchronization algorithm

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international Workshop on Test and Evaluation of Programmable Networks (TEPN 22) Message from the Workshop Chairs

Proceedings - 18th Annual International Conference on Distri...

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Proceedings - 18th annual international conference on distributed computing in sensor systems, dcoss 2022 2022年 XXII页

作者： Afghah, Fatemeh Wang, K.C. Ravi, Srivatsan Schwab, Stephen

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the Fourth international Workshop on "Wireless sensors and Drones in Internet of things" (Wi-DroIT 2022) Message from the Workshop Chairs

Proceedings - 18th Annual International Conference on Distri...

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Proceedings - 18th annual international conference on distributed computing in sensor systems, dcoss 2022 2022年 XVIII页

作者： Sorbelli, Francesco Betti Saad, Walid Wang, Lu

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Message from the IoTI4 2022 Workshop Chairs

Proceedings - 18th Annual International Conference on Distri...

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Proceedings - 18th annual international conference on distributed computing in sensor systems, dcoss 2022 2022年 XVII页

作者： Lagkas, thomas Sarigiannidis, Panagiotis Soldatos, John International Hellenic University Greece University of Western Macedonia Greece Netcompany-Intrasoft Luxembourg

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