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Integrating BIM and IoT Technologies in Innovative Fire Management systems

Integrating BIM and IoT Technologies in Innovative Fire Mana...

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International Multidisciplinary conference on Computer and Energy Science (SpliTech)

作者： Ilaria Sergi Ada Malagnino Roberto Conte Rosito Vincenzo Lacasa Angelo Corallo Luigi Patrono University of Salento Lecce Italy ITS s.r.l. Matera Italy

ISBN: (数字)9789532901054

ISBN: (纸本)9781728173634

In emergency situations, such as building fires, the rescue team must quickly undertake the most appropriate intervention strategy aimed at preventing loss of human life. Emerging hardware and software technologies such as sensors, embedded systems, drones, lidar, Cloud, Artificial Intelligence and Building Information Modeling tools, offer exceptional opportunities in this context. In particular, the attempt to combine and integrate the Internet of things technologies with Building Information Modeling tools is very interesting in the context of future smart cities. In this paper, a potential integration proposal between Building Information Modeling tools and Internet of things technologies for fire prevention and emergency management has been presented. the architecture system has been described and a simple functional validation of the proposed system has been carried out. Finally, a discussion about the advantages of this integration for the creation of innovative systems for fire safety in buildings has been tackled.

关键词： Smart cities Buildings Tools Software sensor systems Internet of things Context modeling

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Poster Abstract: Image Compression Task Coordination Mechanism Based on Dynamic Alliance in Mobile Wireless Multimedia sensor Networks 16

Poster Abstract: Image Compression Task Coordination Mechani...

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16th conference on embedded networked sensor systems (SENSYS)

作者： Li, He Xiao, Tian Lan, Yihua Qi, Qinglei Liu, Quan Liu, Jinjang Nanyang Normal Univ Sch Comp & Informat Technol Nanyang Peoples R China Nanyang Med Coll Dept Hlth Management Nanyang Peoples R China Xian Xinnengda Elect Technol Co Ltd Xian Shaanxi Peoples R China

ISBN: (纸本)9781450359528

In mobile wireless multimedia sensor networks (MWMSNs) image compression task coordination, the existing methods without considering the dynamic changes of the processing ability and location of cooperative nodes, which will cause frequent interruptions of image compression tasks and task data re-transmission. To solve these problems, an image compression task cooperation algorithm based on dynamic alliance (ATDA) is proposed. the image compression task is divided into image transfer subtask and image compression subtask based on the task stable execution time and the principles and constraints of task decomposition. Simulation results show that the proposed algorithm can realize the task load balancing of the alliance collaboration nodes and reduce the execution time of the image compression task and energy consumption.

关键词： Mobile multimedia sensor networks Image compression Task collaboration

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Fabric as a sensor: Towards Unobtrusive Sensing of Human Behavior with Triboelectric Textiles 18

Fabric as a Sensor: Towards Unobtrusive Sensing of Human Beh...

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16th conference on embedded networked sensor systems (SENSYS)

作者： Kiaghadi, Ali Baima, Morgan Gummeson, Jeremy Andrew, Trisha Ganesan, Deepak Univ Massachusetts Coll Informat & Comp Sci Amherst MA 01003 USA Univ Massachusetts Dept Chem Amherst MA 01003 USA

ISBN: (纸本)9781450359528

Smart apparel with embedded sensors have the potential to revolutionize human behavior sensing by leveraging everyday clothing as the sensing substrate. However, existing textile-based sensing techniques rely on tight-fitting garments to obtain sufficient signal to noise, making it uncomfortable to wear and limiting the technology to niche applications like athletic performance monitoring. Our solution leverages functionalized fabric to measure the triboelectric charges induced by folding and compression of the textile itself, making it a more natural fit for everyday clothing. However, the large sensing surface of a functionalized textile also increases body-coupled noise and motion artifacts, and introduces new challenges in how we suppress noise to detect the weak triboelectric signal. We address these challenges using a combination of textile, electronics, and signal analysis-based innovations, and robustly sense joint motions by improving SNR and extracting highly discriminative features from the signal. Additionally, we demonstrate how the same sensor can be used to measure relative changes in skin moisture levels induced by sweating. Our design uses a simple-to-manufacture layered architecture that can be incorporated into any conventional, loosely worn textile. We show that the sensor has high performance in natural conditions by benchmarking the accuracy of sensing several kinematic metrics as well as sweat level. Additionally, we provide real-world performance evaluations across three application case studies including activity classification, perspiration measurements during exercise, and comfort level detection for HVAC systems.

关键词： Ubiquitous sensing smart textile

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Fall-curve: A novel primitive for IoT Fault Detection and Isolation 18

Fall-curve: A novel primitive for IoT Fault Detection and Is...

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16th conference on embedded networked sensor systems (SENSYS)

作者： Chakraborty, Tusher Nambi, Akshay Uttama Chandra, Ranveer Sharma, Rahul Swaminathan, Manohar Kapetanovic, Zerina Appavoo, Jonathan Microsoft Res Redmond WA 98052 USA

ISBN: (纸本)9781450359528

the proliferation of Internet of things (IoT) devices has led to the deployment of various types of sensors in the homes, offices, buildings, lawns, cities, and even in agricultural farms. Since IoT applications rely on the fidelity of data reported by the sensors, it is important to detect a faulty sensor and isolate the cause of the fault. Existing fault detection techniques demand sensor domain knowledge along with the contextual information and historical data from similar near-by sensors. However, detecting a sensor fault by analyzing just the sensor data is non-trivial since a faulty sensor reading could mimic non-faulty sensor data. this paper presents a novel primitive, which we call the Fall-curve - a sensor's voltage response when the power is turned off - that can be used to characterize sensor faults. the Fall-curve constitutes a unique signature independent of the phenomenon being monitored which can be used to identify the sensor and determine whether the sensor is correctly operating. We have empirically evaluated the Fall-curve technique on a wide variety of analog and digital sensors. We have also been running this system live in a few agricultural farms, with over 20 IoT devices. We were able to detect and isolate faults with an accuracy over 99%, which would have otherwise been hard to detect only by observing measured sensor data.

关键词： IoT system Fault detection Fault isolation sensor identification Analog and Digital sensors, Reliability

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Secret Key based sensor Node Security in the Internet of things (IoT)

Secret Key based Sensor Node Security in the Internet of Thi...

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International conference on Communication and Electronics systems (ICCES)

作者： Timothy Malche Priti Maheshwary Rakesh Kumar Rabindranath Tagore University (formerly AISECT University) Raisen MP INDIA Sagar Institute of Research & Technology BHOPAL MP INDIA

ISBN: (数字)9781728153711

ISBN: (纸本)9781728153728

Security in Internet of things (IoT) deals with safeguarding connected objects and networks. IoT involves the growing collection of objects known as things with unique identifiers. these objects have the ability to automatically transfer data over a network. Most of the increase in IoT communication comes from computing devices and embedded sensor systems which are used in industrial machine-to-machine (M2M) communication, home and building automation, vehicle to vehicle communication, smart energy grids, and wearable devices. Because the idea is to connect all physical objects to Internet, security has not always been measured in product design. the IoT products fail to select sufficiently strong security. therefore, security is one of the important factors in IoT that should be taken care on priority basis. this study proposes IoT architecture which deals with security of devices. the main aim of this study is to make sure that an authentic device uploads the data and restrict false data being uploaded by devices trying to be an authentic device. the study presents a strong authentication technique based on secret keys which protects the identity of IoT devices in the network. the authentication and authorization techniques presented in this paper ensure that the right data is sent and received by right devices at right places and for right purpose.

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FastDeepIoT: Towards Understanding and Optimizing Neural Network Execution Time on Mobile and embedded Devices 18

FastDeepIoT: Towards Understanding and Optimizing Neural Net...

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16th conference on embedded networked sensor systems (SENSYS)

作者： Yao, Shuochao Zhao, Yiran Shao, Huajie Liu, ShengZhong Liu, Dongxin Su, Lu Abdelzaher, Tarek Univ Illinois Urbana IL 61801 USA SYNY Buffalo Buffalo NY USA

ISBN: (纸本)9781450359528

Deep neural networks show great potential as solutions to many sensing application problems, but their excessive resource demand slows down execution time, pausing a serious impediment to deployment on low-end devices. To address this challenge, recent literature focused on compressing neural network size to improve performance. We show that changing neural network size does not proportionally affect performance attributes of interest, such as execution time. Rather, extreme run-time nonlinearities exist over the network configuration space. Hence, we propose a novel framework, called FastDeepIoT, that uncovers the non-linear relation between neural network structure and execution time, then exploits that understanding to find network configurations that significantly improve the trade-off between execution time and accuracy on mobile and embedded devices. FastDeepIoT makes two key contributions. First, FastDeepIoT automatically learns an accurate and highly interpretable execution time model for deep neural networks on the target device. this is done without prior knowledge of either the hardware specifications or the detailed implementation of the used deep learning library. Second, FastDeepIoT informs a compression algorithm how to minimize execution time on the profiled device without impacting accuracy. We evaluate FastDeepIoT using three different sensing-related tasks on two mobile devices: Nexus 5 and Galaxy Nexus. FastDeepIoT further reduces the neural network execution time by 48% to 78% and energy consumption by 37% to 69% compared with the state-of-the-art compression algorithms.

关键词： Deep Learning Execution Time Model Compression Mobile Computing Internet of things

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Continuous Low-Power Ammonia Monitoring Using Long Short-Term Memory Neural Networks 18

Continuous Low-Power Ammonia Monitoring Using Long Short-Ter...

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16th conference on embedded networked sensor systems (SENSYS)

作者： Jia, Zhenhua Lyu, Xinmeng Zhang, Wuyang Martin, Richard P. Howard, Richard E. Zhang, Yanyong Rutgers State Univ Wireless Informat Network Lab North Brunswick Township NJ 08902 USA

ISBN: (纸本)9781450359528

Accurate and continuous ammonia monitoring is important for laboratory animal studies and many other applications. Existing solutions are often expensive, inaccurate, or unsuitable for long-term monitoring. In this work, we propose a new ammonia monitoring approach that is low-power, automatic, accurate, and wireless. Our system uses metal oxide sensors which change their electrical resistance due to an induced reduction reaction with ammonia at high temperatures. Traditional methods infer the ammonia level by measuring the sensor's electrical resistance after it reaches equilibrium. Such a system consumes a significant amount of energy because reaching equilibrium requires heating the sensor for minutes. Our proposed approach does not wait for equilibrium, but tries to predict the resistance at equilibrium using the sensor's initial resistance response curve in a very short heating pulse (as short as 200ms). the prediction model is built on long short-term memory (LSTM) neural networks. We built 38 prototype sensors and a home-grown gas flow system. In a 3-month in-lab testing period, we conducted extensive experiments and collected 13,770 measurements. Our model accurately predicts the equilibrium state resistance value, with an average error rate of 0.12%. the final average estimation error for the ammonia concentration level is 9.38ppm. Given the ultra low power consumption and accurate measurements, we have partnered with cage vendors and deployed our system at two animal research facilities (NIH and Cornell University) for month-long medical trials.

关键词： Ammonia sensor Low-power Transient Response Long Short-term Memory Neural Networks

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Design of Landslide Warning System 5th

Design of Landslide Warning System

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5th International conference of Pioneer Computer Scientists, Engineers and Educators, ICPCSEE 2019

作者： Yang, Xiaoping Du, Jixuan Su, Zhaoyu Nong, Pubin Qin, Zhirong Chen, Bailin College of Information Science and Engineering Guilin University of Technology Guilin541004 China Guangxi Key Laboratory of Embedded Technology and Intelligent System Guilin541004 China

ISBN: (纸本)9789811501203

Aiming at geological disaster monitoring and prevention work, a real-time monitoring and early warning system is proposed for low-power consumption of landslides to meet the needs of landslide monitoring in remote mountainous areas. the inclination angle of the mountain body was detected by a mechanical inclination sensor, and a plurality of inclination sensors were placed on each landslide body to form an array distribution. the landslide body was stereoscopically monitored. Each mesh node had a different node address, and different inclination thresholds were set in advance. When the sensor detection value reached the threshold, an alarm message was sent to the system main control end, and the main control end generated an audible and visual alarm, and an alarm message was sent at the same time. Compared with the current landslide warning system on the market, the system achieves expected results and its power consumption is extremely low. the sensor terminal of the mountain monitoring is powered by dry battery and can work for 6 years in the field without external power supply. It avoids the damages made by weather, livestock and human, and has broad application prospects. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Alarm systems

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Smart Stick for Elderly 12

Smart Stick for Elderly

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IEEE Int Congr on Cybermat / 12th IEEE Int Conf on Cyber, Phys and Social Comp (CPSCom) / 15th IEEE Int Conf on Green Computing and Communications (GreenCom) / 12th IEEE Int Conf on Internet of things (ithings) / 5th IEEE Int Conf on Smart Data

作者： Boppana, Lakshmi Jain, Vishal Kishore, Ravi Natl Inst Technol Dept Elect & Commun Engn Warangal Andhra Pradesh India

ISBN: (纸本)9781728129808

In the past few decades, the technology boom has unleashed an enormous potential to explore and implement various assistive devices for the elderly to lead their life independently. In this paper, we present the design and implementation of a prototype which would serve as an efficient aid for the elderly and people with Alzheimer's in mild stage. this stick is embedded with various features making it a Smart walking stick. this walking stick can monitor various health parameters and informs the nearby primary health center and caretaker of any abnormalities. this smart stick can also help elder persons to reach home safely if they lost themselves when go out alone. the proposed stick can also be used to control home appliances and to remind the user for taking the medicine on time. this prototype is designed using a low cost Wi-Fi chip with TCP/IP stack and Microcontroller produced by Espressif systems for implementing controller functionality and the appropriate sensors. All the modules of proposed smart stick along with the battery must be concealed inside the stick to reduce the risk of damage to the circuit and look elegant. this stick is tested to verify the functionality of all features and this would be very useful for elders to restore their confidence and increase mobility when compared to the conventional sticks available in the market only for walking.

关键词： GSM GPS IR LED pulse rate sensor RFID strip temperature

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acm International conference Proceeding Series

ACM International Conference Proceeding Series

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5th Workshop on Cryptography and Security in Computing systems, CS2 2018, in conjunction with the 13th High Performance and embedded Architecture and Compilation, HiPEAC 2018

ISBN: (纸本)9781450363747

the proceedings contain 4 papers. the topics discussed include: speeding up Curve25519 using toeplitz matrix-vector multiplication;exploring the vulnerability of R-LWE encryption to fault attacks;TinyWIDS: a WPM-based intrusion detection system for TinyOS2.x/802.15.4 wireless sensor networks;and all paths lead to Rome: polymorphism runtime code generation for embedded systems.

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