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检索条件"任意字段=Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems"

共 81 条记录，以下是11-20 订阅

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Demo: Hardware to unleash novel energy sources for outdoor sensor networks 25

Demo: Hardware to unleash novel energy sources for outdoor s...

引用

proceedings of the 23rd acm conference on embedded networked sensor systems

作者： Alec Levy John Madden Mirella Pessoa de Melo Colleen Josephson UC Santa Cruz Santa Cruz USA

ISBN: (纸本)9798400714795

We present a demonstration of a wireless sensor network system to measure power output from nontraditional low-power energy sources. Our system has the necessary measurement fidelity for logging power traces and environmental data to a web based measurement portal and facilitates transition from in-lab experiments to the field. Our demonstration shows different use cases of our system by logging various energy sources: a soil-based microbial fuel cell, a prickly pear cactus, and a thermoelectric generator. A large screen will be used to continuously display live data traces.

关键词： wireless sensor networks

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F2Zip: Finetuning-Free Model Compression for Scenario-Adaptive embedded Vision 24

F2Zip: Finetuning-Free Model Compression for Scenario-Adapti...

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22nd acm conference on embedded networked sensor systems, SenSys 2024

作者： Luo, Puhan Hou, Jiahui Yuan, Mu Wu, Guangyu Yao, Yunhao Li, Xiang-Yang University of Science and Technology of China Hefei China

ISBN: (纸本)9798400706974

With the development of the Internet of Things and artificial intelligence, the deployment and inference of intelligent models have gradually raised concerns. To reduce the huge computation and storage overhead of modern deep neural networks, many studies use model pruning techniques to reduce the model size and computational cost. However, existing pruning techniques usually require model fine-tuning, which incurs high additional overhead, making them difficult to apply to real-world scenarios. In this work, we focus on vision model compression and present F2Zip, a scenario-adaptive finetuning-free pruning framework for embedded devices. First, we propose a scenario complexity measurement that quantifies scenario changes with pixel-level entropy. By analyzing the scenario complexity, F2Zip adaptively evaluates the importance of different channels and layers of the model using only a small amount (tens) of unlabeled data. Then we design a multi-constraint knapsack solver to prune scenario-unrelated redundant channels. We implemented and deployed F2Zip in surveillance scenarios and tested different models on videos collected from both public and real-world sources. Experimental results show that F2Zip is free of model fine-tuning in various scenarios. F2Zip reduces the end-to-end deployment time by 89.8% and reduces energy cost by 79.5%, which shows that F2Zip is computationally friendly for embedded devices. Without fine-tuning and any accuracy degradation, F2Zip achieves up to 50.2% parameter reduction, outperforming baseline methods by 35.1%. © 2024 Copyright is held by the owner/author(s).

关键词： Deep neural networks

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Poster Abstract: Fine-grained Contextualized Activity Logs Generation based on Multi-Modal sensor Data and LLM 25

Poster Abstract: Fine-grained Contextualized Activity Logs G...

引用

proceedings of the 23rd acm conference on embedded networked sensor systems

作者： Ye Tian Onat Gungor Xiaofan Yu Tajana Rosing University of California San Diego La Jolla California USA University of California San Diego La Jolla USA

ISBN: (纸本)9798400714795

Detailed activity logs are crucial for health monitoring and personalized interventions. Traditional methods rely on manual editing or raise privacy concerns due to the use of camera recordings. This paper proposes ContextLLM, an innovative system that utilizes a large language model (LLM) to understand sensor data from smartphones and smartwatches and automatically generate contextualized activity logs. Compared to the state-of-the-art, it incorporates key contextual information and physiological indicators, enabling more fine-grained semantic descriptions. Preliminary results show that the automatically generated activity logs achieve 80.26% similarity to human annotations, demonstrating the feasibility.

关键词： cyber-physical systems

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Demo Abstract - SIGAR: sensor Integration Gateway using Augmented Reality 25

Demo Abstract - SIGAR: Sensor Integration Gateway using Augm...

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proceedings of the 23rd acm conference on embedded networked sensor systems

作者： Ishan Bansal Nagarjun Bhat Agrim Gupta Harine Govindarajan Dinesh Bharadia University of California San Diego La Jolla USA

ISBN: (纸本)9798400714795

We introduce SIGAR, a sensor Integration Gateway using Augmented Reality, which combines RFID-based passive sensing with AR for real-time visualization. Using batteryless, wireless RFID sensors, SIGAR eliminates the need for power sources, enabling sustainable and cost-effective monitoring. A mobile app automatically detects sensors within the camera's field of view and overlays realtime sensory data onto the physical environment. Demonstrated through applications like force, soil moisture and light sensing, SIGAR provides intuitive, context-aware insights for environmental monitoring, inventory management, and more. This fusion of AR and passive sensing bridges digital and physical worlds, offering scalable, low-power IoT solutions.

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Poster Abstract : A Structural Vibration-based Gait Abnormality Detection system 25

Poster Abstract : A Structural Vibration-based Gait Abnormal...

引用

proceedings of the 23rd acm conference on embedded networked sensor systems

作者： Mainak Chakraborty Bodhibrata Mukhopadhyay Subrat Kar Embedded Lab IIT Delhi New Delhi India IIT Roorke Roorkee India IIT Delhi New Delhi India

ISBN: (纸本)9798400714795

Gait recognition based on structural vibration signals is an emerging area in soft biometrics and healthcare. It is valued for its privacy-preserving features, making it ideal for continuous monitoring in healthcare environments. In this work, we propose a method for simultaneous person identification and gait-abnormality detection using structural vibration signals. We have experimented on a dataset of eight people. The system uses shared feature extraction layers with separate branches for identification and abnormality detection. Our framework achieves a person identification accuracy of ~89.00% and ~90.00% accuracy in detecting abnormality in gait patterns.

关键词： structural vibration

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OpenIoT-Lab1: an Open Source cost-efficient sensor based Fog-IoT Testbed: An initial prototype 25

OpenIoT-Lab1: an Open Source cost-efficient sensor based Fog...

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proceedings of the 23rd acm conference on embedded networked sensor systems

作者： Sahil Kumar Jagpreet Singh Amit Kumar Dhar Vishal Krishna Singh Research Scholar Ropar Punjab India Assistant Professor Ropar India Assistant Professor Bhilai India Lecturer Colchester United Kingdom

ISBN: (纸本)9798400714795

The need for reliable test environments grows as IoT applications become more complex. The hardware testbeds are crucial for evaluating network protocols, device interoperability, security mechanisms, and performance optimization. However, because of the growing demand, most state-of-the-art IoT testbeds are either not available or are costly and are not open-source for reproduction. In this paper, we propose OpenIoT-Lab1, which uses low-cost devices, and with its code available online, it can be easily reproduced at scale in various industries and academic institutions to support research in sensor networks and Fog/IoT networks.

关键词： IoT

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Invasive insect pest monitoring using low-cost, field deployable, machine-learning-assisted sensor systems 14

Invasive insect pest monitoring using low-cost, field deploy...

引用

conference on Bioinspiration, Biomimetics, and Bioreplication XIV

作者： McNeill, Seth A. Golan, Aviad Shanthan, Heeirthan Mankin, Richard W. Liao, Yabin Embry Riddle Aeronaut Univ 3700 Willow Creek Rd Prescott AZ 86301 USA ARS USDA Ctr Med Agr & Vet Entomol 1700 SW 23rd Dr Gainesville FL 32607 USA

ISBN: (纸本)9781510671959;9781510671942

The Asian citrus psyllid (ACP), Diaphorina citri Kuwayama (Hemiptera: Liviidae), is a citrus pest that vectors the bacterium that causes huanglongbing (HLB) disease between citrus trees. It has become a very large problem to the US citrus growers. Male ACP find females by vibrating the substrate (branch) to call them. The females vibrate a response and the males track these responses to find them in a citrus tree. We have created three ACP call recognition systems{one using Matlab, one using TensorFlow implemented on a Raspberry Pi, and one using Edge Impulse implemented on a RP2040 microcontroller. All three systems recognized calls with an accuracy greater than 79.5%. A demonstration on a single, long recording of two ACP vibrating to each other using the RP2040 system shows that it would be useful in a live implementation.

关键词： machine learning embedded systems insect detection vibration acoustic microcontroller psyllid

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Poster Abstract: Autonomous AI-Driven Grid Protection: Sub-Cycle Fault Response via NPU-Optimized Neural Networks 25

Poster Abstract: Autonomous AI-Driven Grid Protection: Sub-C...

引用

proceedings of the 23rd acm conference on embedded networked sensor systems

作者： Aleksandr Kovalenko Aleksey Evdakov Galina Filatova Andrey Yablokov Aleksandr Bulashov Ilya Makarov AIRI Moscow Russian Federation LLC Moscow Russian Federation ISPU Ivanovo Russian Federation TISBI Kazan Russian Federation ISP RAS Moscow Russian Federation ITMO University Saunt-Petersburg Russian Federation

ISBN: (纸本)9798400714795

Relay Protection and Automation (RPA) devices maintain power system stability by isolating faults using predefined or adaptive thresholds. However, even flexible configurations require manual pre-tuning, limiting their adaptability in dynamic grid environments, such as those with renewable energy integration. Artificial Intelligence (AI) augments RPA functionality by generalizing to new, unseen data, improving fault detection accuracy in transient or noisy scenarios. Our early studies demonstrate that embedded AI systems outperform static thresholds while operating in real time. These systems, implemented via neural networks on System-on-Chip (SoC) platforms with dedicated Neural Processing Units (NPUs), avoid cloud-dependent latency.

关键词： embedded AI

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A Sustainable Scalable Self-configurable sensor-based IoT Network 25

A Sustainable Scalable Self-configurable Sensor-based IoT Ne...

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proceedings of the 23rd acm conference on embedded networked sensor systems

作者： Sahil Kumar Asad Alam Shiva Koshta Jagpreet Singh CSE IIT Ropar Ropar Punjab India

ISBN: (纸本)9798400714795

With an increasing demand for IoT applications, powering these nodes has become challenging. Delivering power to IoT nodes with energy harvesting is a promising solution. Solar, among many harvesting approaches, is emerging for both indoor and outdoor applications. However, most of the published solutions with solar harvesting are single-node solutions for short and long-range communication. The primary challenge for developing scalable and self-configurable sustainable networks is the intermittent operation of the IoT nodes due to the non-availability of required power. In this paper, we demonstrate a cost-efficient solar-powered multi-hop self-configurable sensor network for future IoT applications. One of our proposed solutions can harvest 420 mW power and hence can support multiple sensors as well; however, it does not store any power. Another design is more stable with an onboard supercapacitor but can harvest a max of 80 mW. Both of these solutions are able to power nodes continuously in outdoor settings and hence develop a scalable network. We also propose a compact, cost-effective, rugged version of the solar-powered IoT sensor node.

关键词： IoT

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Toward sensor-In-the-Loop LLM Agent: Benchmarks and Implications 25

Toward Sensor-In-the-Loop LLM Agent: Benchmarks and Implicat...

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proceedings of the 23rd acm conference on embedded networked sensor systems

作者： Zhiwei Ren Junbo Li Minjia Zhang Di Wang Xiaoran Fan Longfei Shangguan University of Pittsburgh Pittsburgh PA USA University of Illinois Urbana-Champagin Champaign IL USA Independent Researcher Seattle WA USA Google Mountain View CA USA

ISBN: (纸本)9798400714795

This paper explores sensor-informed personal agents that can take advantage of sensor hints on wearables to enhance the personal agent's response. We demonstrate that such a sensor-in-the-loop AI agent design can be easily integrated into existing LLM agents by building a prototype named WellMax based on existing well-developed techniques such as structured prompt templates and few-shot prompting. The head-to-head comparison with a non-sensor-informed agent across five use scenarios demonstrates that this sensor-in-the-loop design can effectively improve users' needs and their overall experience. The deep-dive into agents' replies and participants' feedback further reveals that sensor-in-the-loop agents not only provide more contextually relevant responses but also exhibit a better understanding of user priorities and situational nuances. In addition, we conduct two case studies to examine the potential pitfalls and distill key insights from this sensor-in-the-loop agent. We hope this work can spawn new ideas for building more intelligent, empathetic, and effective AI-driven personal assistants.

关键词： context-aware LLMs

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