Towards Robust Synchronization in IoT Networks

Gore, Rahul; Elizabeth, Namita; Dzung, Dacfey; Ashok, S.

doi:10.1109/comsnets.2019.8711343

Cited by 7 publications

(2 citation statements)

References 6 publications

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“…Strain signal prediction requires accurate synchronization between all sensors at high sampling rates, especially for fully wireless sensors. However, such protocols [15,16,17,18,19] can be costly and power consuming. To address this problem, the decoder network shown in Fig.…”

Section: Fully Neural Bwimmentioning

confidence: 99%

Fully-Neural Approach to Vehicle Weighing and Strain Prediction on Bridges Using Wireless Accelerometers

Kawakatsu

Aihara

Takasu

et al. 2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Bridge weigh-in-motion (BWIM) is a technique of estimating vehicle loads on bridges and can be used to assess a bridge's structural fatigue and therefore its life. BWIM can be realized by analyzing the bridge deflection in terms of its response to moving axle loads. To obtain accurate load estimates, current BWIM systems require strain sensors, whose (re-) installation costs have limited their application. In this paper, we propose a new BWIM approach based on a deep neural network using accelerometers, which are easier to install than strain sensors, thus helping the advancement of low-cost BWIM systems. By learning the bridge dynamism, our model estimates axle loads successfully from the noisy acceleration signals sampled on a real bridge in service.

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Section: Fully Neural Bwimmentioning

confidence: 99%

Fully-Neural Approach to Vehicle Weighing and Strain Prediction on Bridges Using Wireless Accelerometers

Kawakatsu

Aihara

Takasu

et al. 2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…An event detection unit u will issue an ER composed of the ID (y) of all detected events, a timestamp ts of the moment it was created and the GPS coordinates of the EDU (latitude, la, and longitude, lo). The timestamp is important because it informs the EACs about the moment the events were detected (e.g., using a 64-bit UTC notation) and the proposed CityAlarm system may use some time synchronization protocol to make this information consistent [35] (although this is not a requirement). Moreover, the GPS coordinates of the EDU not only tell the location of the detected events, but also allow the EDU to be mobile, making it more effective at dynamically retrieving such coordinates from a GPS hardware module than if it just relayed information on the preconfigured location of the EDU.…”

Section: Event Reportsmentioning

confidence: 99%

A Distributed Multi-Tier Emergency Alerting System Exploiting Sensors-Based Event Detection to Support Smart City Applications

Costa

Vasques

Portugal

et al. 2019

Sensors

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The development of efficient sensing technologies and the maturation of the Internet of Things (IoT) paradigm and related protocols have considerably fostered the expansion of sensor-based monitoring applications. A great number of those applications has been developed to monitor a set of information for better perception of the environment, with some of them being dedicated to identifying emergency situations. Current IoT-based emergency systems have limitations when considering the broader scope of smart cities, exploiting one or just a few monitoring variables or even allocating high computational burden to regular sensor nodes. In this context, we propose a distributed multi-tier emergency alerting system built around a number of sensor-based event detection units, providing real-time georeferenced information about the occurrence of critical events, while taking as input a configurable number of different scalar sensors and GPS data. The proposed system could then be used to detect and to deliver emergency alarms, which are computed based on the detected events, the previously known risk level of the affected areas and temporal information. Doing so, modularized and flexible perceptions of critical events are provided, according to the particularities of each considered smart city scenario. Besides implementing the proposed system in open-source electronic platforms, we also created a real-time visualization application to dynamically display emergency alarms on a map, demonstrating a feasible and useful application of the system as a supporting service. Therefore, this innovative approach and its corresponding physical implementation can bring valuable results for smart cities, potentially supporting the development of adaptive IoT-based emergency-aware applications.

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Blockchain-based trust management for verifiable time synchronization service in IoT

Fan

Shi

et al. 2022

Peer-to-Peer Netw. Appl.

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Towards Robust Synchronization in IoT Networks

Cited by 7 publications

References 6 publications

Fully-Neural Approach to Vehicle Weighing and Strain Prediction on Bridges Using Wireless Accelerometers

Fully-Neural Approach to Vehicle Weighing and Strain Prediction on Bridges Using Wireless Accelerometers

A Distributed Multi-Tier Emergency Alerting System Exploiting Sensors-Based Event Detection to Support Smart City Applications

Blockchain-based trust management for verifiable time synchronization service in IoT

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