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through-Screen Visible Light Sensing Empowered by embedded Deep Learning 21

Through-Screen Visible Light Sensing Empowered by Embedded D...

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19th acm conference on embedded networked sensor systems, SenSys 2021

作者： Liu, Hao Ye, Hanting Yang, Jie Wang, Qing Delft University of Technology Delft Netherlands

ISBN: (纸本)9781450390972

Motivated by the trend of realizing full screens on devices such as smartphones, in this work we propose through-screen sensing with visible light for the application of fingertip air-writing. the system can recognize handwritten digits with under-screen photodiodes as the receiver. the key idea is to recognize the weak light reflected by the finger when the finger writes the digits on top of a screen. the proposed air-writing system has immunity to scene changes because it has a fixed screen light source. However, the screen is a double-edged sword as both a signal source and a noise source. We propose a data preprocessing method to reduce the interference of the screen as a noise source. We design an embedded deep learning model, a customized model ConvRNN, to model the spatial and temporal patterns in the dynamic and weak reflected signal for air-writing digits recognition. the evaluation results show that our through-screen fingertip air-writing system with visible light can achieve accuracy up to 91%. Results further show that the size of the customized ConvRNN model can be reduced by 94% with less than a 10% drop in performance. © 2021 Owner/Author.

关键词： Light sources

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Capricorn: Towards Real-time Rich Scene Analysis Using RF-Vision sensor Fusion 20

Capricorn: Towards Real-time Rich Scene Analysis Using RF-Vi...

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20th acm conference on embedded networked sensor systems (SenSys)

作者： Wang, Ziqi Sarker, Ankur Wu, Jason Hua, Derek Dong, Gaofeng Singh, Akash Deep Srivastava, Mani Univ Calif Los Angeles Elect & Comp Engn Dept Los Angeles CA 90095 USA

ISBN: (纸本)9781450398862

Video scene analysis is a well-investigated area where researchers have devoted efforts to detect and classify people and objects in the scene. However, real-life scenes are more complex: the intrinsic states of the objects (e.g., machine operating states or human vital signals) are often overlooked by vision-based scene analysis. Recent work has proposed a radio frequency (RF) sensing technique, wireless vibrometry, that employs wireless signals to sense subtle vibrations from the objects and infer their internal states. We envision that the combination of video scene analysis with wireless vibrometry form a more comprehensive understanding of the scene, namely "rich scene analysis". However, the RF sensors used in wireless vibrometry only provide time series, and it is challenging to associate these time series data with multiple real-world objects. We propose a real-time RF-vision sensor fusion system, Capricorn, that efficiently builds a cross-modal correspondence between visual pixels and RF time series to better understand the complex natures of a scene. the vision sensors in Capricorn model the surrounding environment in 3D and obtain the distances of different objects. In the RF domain, the distance is proportional to the signal time-of-flight (ToF), and we can leverage the ToF to separate the RF time series corresponding to each object. the RF-vision sensor fusion in Capricorn brings multiple benefits. the vision sensors provide environmental contexts to guide the processing of RF data, which helps us select the most appropriate algorithms and models. Meanwhile, the RF sensor yields additional information that is originally invisible to vision sensors, providing insight into objects' intrinsic states. Our extensive evaluations show that Capricorn real-timely monitors multiple appliances' operating status with an accuracy of 97%+ and recovers vital signals like respirations from multiple people. A video (https: //***/b-5nav3Fi78) demonstrates the capabi

关键词： Time series

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Firefly: Localizing Drones with Visible Light Communication and sensor Fusion 19

Firefly: Localizing Drones with Visible Light Communication ...

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19th Annual International conference on Distributed Computing in Smart systems and the Internet of things, DCOSS-IoT 2023

作者： Hernandez, Ricardo Ampudia Xu, Talia Huang, Yanqiu Zuniga Zamalloa, Marco A. University of Twente Department of Computer Science Netherlands Tu Delft Department of Computer Science Netherlands

ISBN: (纸本)9798350346497

In this paper, we propose a new approach where drones attain accurate localization by fusing information from artificial lighting and their embedded inertial and barometer sensors. Our system is able to provide accurate drone localization without the use of radios, GPS or cameras. We evaluate our framework, dubbed Firefly, with a testbed consisting of four light beacons and a mini-drone. Our results show that Firefly allows locating the drone within a few decimeters of the actual position;and compared to two state-of-the-art positioning methods that rely solely on lighting information, Firefly can reduce the localization error by 50 % and 80%.. respectively. © 2023 IEEE.

关键词： Drones

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sensor Virtualization for Efficient Sharing of Mobile and Wearable sensors 21

Sensor Virtualization for Efficient Sharing of Mobile and We...

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19th acm conference on embedded networked sensor systems, SenSys 2021

作者： Xu, Jian Bhattacharya, Arani Balasubramanian, Aruna Porter, Donald E. Stony Brook University United States IIIT-Delhi India UNC Chapel Hill United States

ISBN: (纸本)9781450390972

Users are surrounded by sensors that are available through various devices beyond their smartphones. However, these sensors are not fully utilized by current end-user applications. A key reason sensor use is so limited is that application developers must exactly identify how the sensor data can be used by smartphone apps. To mitigate this problem, we present SenseWear, a sensor-sharing platform that extends the functionality of a smartphone to use remote sensors with limited additional developer effort. sensor sharing has several uses, including augmenting the hardware in smartphones, creating new gestural interactions with smartphone applications, and improving application's Quality of Experience via higher-quality sensors from other devices, such as wearables. We developed and present six use cases that use remote sensors in various smartphone applications. Each extension requires adding fewer than 20 lines of code on average. Furthermore, using remote sensors did not introduce a perceptible increase in latency, and creates more convenient interaction options for smartphone apps. © 2021 acm.

关键词： Smartphones

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Six-Layer Industrial Architecture Applied to Predictive Maintenance

Six-Layer Industrial Architecture Applied to Predictive Main...

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19th International conference on Software Technologies, ICSOFT 2024

作者： Guidotti, Fernanda Pereira Arantes, Jesimar da Silva da Silva Arantes, Márcio Bedoya, Albeiro Espinosa Motta Toledo, Claudio Fabiano Institute of Mathematics and Computer Science University of Sao Paulo São Carlos Brazil Institute of Exact and Technological Sciences University of Lavras Lavras Brazil SENAI Institute for Innovation in Embedded Systems ISI-SE Florianopolis Brazil Department of Computer Science and Decision University of Colombia Medellin Colombia

ISBN: (纸本)9789897587061

In the context of digital transformation defining Industry 4.0, the integration of Industrial Artificial Intelligence (I-AI) emerges as a transformative element, promoting the development, validation, and deployment of machine learning algorithms in industrial applications. As sensor technologies advance, reducing costs and expanding the capability for direct data collection from machines, there arises a need for system architectures that not only support but also optimize these data collection and analysis processes. this paper introduces an innovative reference architecture for I-AI, which stands out by advancing beyond the traditional 5-layer (5C) framework through the addition of a sixth layer, named"Consciousness". this innovative layer is designed to retroactively feed the knowledge acquired back to the previous layers, significantly enhancing control and optimization through AI systems. the proposed architecture, termed 6C, comprises the layers of Connection, Conversion, Cyber-Physical, Cognition, Configuration, and finally, Consciousness. the introduction of the Consciousness layer marks a significant innovation in the literature, offering a mechanism by which the architecture is capable of autonomously perceiving the state and needs of the industrial system. Validated in an industrial case study, the 6C architecture demonstrated performance improvement by incorporating the Consciousness layer, highlighting its effectiveness in enhancing operational efficiency and decision-making within complex industrial contexts © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Predictive maintenance

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Acoustic Beacons-based Long-range Localization of Wireless Cameras Drifting in a Narrow Sewer Pipe 22

Acoustic Beacons-based Long-range Localization of Wireless C...

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9th acm International conference on systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys)

作者： Maruyama, Kento Pham, thanh V. Ishihara, Susumu Shizuoka Univ Grad Sch Integrated Sci & Technol Shizuoka Japan Shizuoka Univ Acad Inst Coll Engn Shizuoka Japan

ISBN: (纸本)9781450398909

Screening sewer pipes is an essential task in maintaining city infrastructure. However, it is time and labor-consuming because workers must enter maintenance holes. We have been developing a sewer pipe screening system using drifting networked cameras, which does not require workers to enter into a pipe. Since the coverage of microwave radio communication is short (e.g., about 10 m with 5 GHz IEEE 802.11) in narrow pipes with 200-250 mm diameter, the most popular public sewer pipes in Japan, radio-based localization of drifting cameras is difficult. We propose an acoustic beacon-based long-range localization of drifting cameras moving in a narrow underground pipe. the system takes advantage of the fact that sound waves can be transmitted over long distances through a thin tube, similar to a voice tube. We implemented a system prototype consisting of a drifting unit equipped with a speaker and a receiver unit and conducted experiments in an experimental pipe. the experiment results show that the position estimation error is less than 1 m at a distance of 19 m.

关键词： sensor network inspection system sewer pipe acoustical positioning

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Gapeau: Enhancing the Sense of Distance to Others with a Head-Mounted sensor 22

Gapeau: Enhancing the Sense of Distance to Others with a Hea...

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17th International conference on Tangible, embedded, and Embodied Interaction (TEI)

作者： Wozniak, Mikolaj P. Dominiak, Julia Grudzien, Krzysztof Wrobel-Lachowska, Magdalena Niess, Jasmin Wozniak, Pawel W. Romanowski, Andrzej Carl von Ossietzky Univ Oldenburg Oldenburg Germany Lodz Univ Technol Lodz Poland Univ St Gallen St Gallen Switzerland Chalmers Univ Technol Gothenburg Sweden

ISBN: (纸本)9781450391474

Human perception lacks the capabilities to accurately assess distance. the recent Covid-19 pandemic outbreak rendered this ability particularly important. Augmenting our sense of distance can help maintain safe separation from others when required. To explore how systems can help users maintain physical distance, we designed, implemented and evaluated Gapeau-a head-mounted system for augmenting the sense of distance. Our system uses proximity sensors and thermal sensing to detect and measure the distance to other people. We conducted a validation protocol, an experiment, in which we compared different feedback modalities, and an in-the-wild study to evaluate Gapeau's performance and suitability for use in social contexts. We found that our system enabled users to more accurately determine whether they were maintaining a safe distance from others. Vibration and auditory feedback were found most effective and usable. Gapeau was perceived as socially acceptable. Our work contributes insights for augmented sensing systems with social relevance.

关键词： sensory augmentation head-mounted sensor physical distance wearable computing

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Bus Crowdedness Sensing System Based on Carbon Dioxide Concentration 22

Bus Crowdedness Sensing System Based on Carbon Dioxide Conce...

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proceedings of the 20th acm conference on embedded networked sensor systems

作者： Wenhao Huang Akira Tsuge Yin Chen Tadashi Okoshi Jin Nakazawa Keio University Fujisawa Kanagawa Japan Reitaku University Kashiwa Chiba Japan

ISBN: (纸本)9781450398862

Crowdedness sensing of buses is playing an important role in the disease control of COVID-19 and bus resource scheduling. this research analyzes the relationship between carbon dioxide concentration, bus environment and the number of passengers by linear regression. Our prototype system collects the data of bus environment and carbon dioxide concentration to estimate the number of passengers in real time. By collecting the sensing data from a shuttle bus of university campus, we experimentally evaluate the feasibility and sensing performance of the crowdedness estimation model.

关键词： smart cities crowdedness sensing carbon dioxide sensor ubiquitous computing

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Fuzzy Data Deduplication at Edge Nodes in Connected Environments 19th

Fuzzy Data Deduplication at Edge Nodes in Connected Environm...

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Mobile Web and Intelligent Information systems - 19th International conference, MobiWIS 2023, proceedings

作者： Yakhni, Sylvana Tekli, Joe Mansour, Elio Chbeir, Richard E.C.E. Department Lebanese American University Byblos36 Lebanon Scient Analytics Paris75007 France University of Pau and Pays Adour Anglet64600 France

ISBN: (纸本)9783031397639

the Internet of things (IoT) is ushering-in the era of connected environments, i.e., networks of physical objects that are embedded with sensors and softwar, connecting and exchanging data with other devices and systems. the huge amount of data produced by such systems calls for solutions to reduce the amount of data being handled and transmitted over the network. In this study, we investigate data deduplication as a prominent pre-processing method that can address such a challenge. Data deduplication techniques have been traditionally developed for data storage and data warehousing applications, and aim at identifying and eliminating redundant data items. Few recent approaches have been designed for sensor networks and connected environments, yet existing solutions mostly rely on crisp thresholds and provide minimum-to-no expert control over the deduplication process, disregarding the domain expert’s needs in defining redundancy. In this study, we propose a new approach for Fuzzy Redundancy Elimination for Data Deduplication in a connected environment. We use simple natural language rules to represent domain knowledge and expert preferences regarding data duplication boundaries. We then apply pattern codes and fuzzy reasoning to detect duplicate data items at the outer-most edge (sensor node) level of the network. this reduces the time required to hard-code the deduplication process, while adapting to the domain expert’s needs for different data sources and applications. Experiments on a real-world dataset highlight our solutions’ potential and improvement compared with existing solutions. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： sensor nodes

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Trust-Based Assured sensor Fusion in Distributed Aerial Autonomy 25

Trust-Based Assured Sensor Fusion in Distributed Aerial Auto...

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proceedings of the acm/IEEE 16th International conference on Cyber-Physical systems (with CPS-IoT Week 2025)

作者： R. Spencer Hallyburton Miroslav Pajic Department of Electrical and Computer Engineering Duke University Durham NC USA

ISBN: (纸本)9798400714986

Multi-agent collaboration enhances situational awareness in intelligence, surveillance, and reconnaissance (ISR) missions. Ad hoc networks of unmanned aerial vehicles (UAVs) allow for real-time data sharing, but they face security challenges due to their decentralized nature, making them vulnerable to cyber-physical attacks. this paper introduces a trust-based framework for assured sensor fusion in distributed multi-agent networks, utilizing a hidden Markov model (HMM)-based approach to estimate the trustworthiness of agents and their provided information in a decentralized fashion. Trust-informed data fusion prioritizes fusing data from reliable sources, enhancing resilience and accuracy in contested environments. To evaluate the assured sensor fusion under attacks on system/mission sensing, we present a novel multi-agent aerial dataset built from the Unreal Engine simulator. We demonstrate through case studies improved ISR performance and an ability to detect malicious actors in adversarial settings.

关键词： Autonomous Vehicles

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