scholarly journals Design and Implementation of a Wireless Sensor Network for Seismic Monitoring of Buildings

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3875
Author(s):  
Julio Antonio Jornet-Monteverde ◽  
Juan José Galiana-Merino ◽  
Juan Luis Soler-Llorens
Keyword(s):  
Real Time ◽  
Sensor Network ◽  
Low Cost ◽  
Residential Building ◽  
Internal Clock ◽  
Ambient Vibrations ◽  
Network Resources ◽  
Open Hardware ◽  
Building Monitoring ◽  
Real Time Visualization

This article presents a new wireless seismic sensor network system, especially design for building monitoring. The designed prototype allows remote control, and remote and real-time monitoring of the recorded signals by any internet browser. The system is formed by several Nodes (based on the CC3200 microcontroller of Texas Instruments), which are in charge of digitizing the ambient vibrations registered by three-component seismic sensors and transmitting them to a central server. This server records all the received signals, but also allows their real-time visualization in several remote client browsers thanks to the JavaScript’s Node.js technology. The data transmission uses not only Wi-Fi technology, but also the existing network resources that nowadays can be found usually in any official or residential building (lowering deployment costs). A data synchronization scheme was also implemented to correct the time differences between the Nodes, but also the long-term drifts found in the internal clock of the microcontrollers (improving the quality of records). The completed system is a low-cost, open-hardware and open-software design. The prototype was tested in a real building, recording ambient vibrations in several floors and observing the differences due to the building structure.

scholarly journals Design of a Mobile Low-Cost Sensor Network Using Urban Buses for Real-Time Ubiquitous Noise Monitoring

Sensors ◽  
2016 ◽  
Vol 17 (12) ◽  
pp. 57 ◽  
Author(s):  
Rosa Alsina-Pagès ◽  
Unai Hernandez-Jayo ◽  
Francesc Alías ◽  
Ignacio Angulo
Keyword(s):  
Real Time ◽  
Sensor Network ◽  
Low Cost

Event Processing-based Low-Power Low-Cost Wireless Sensor Network for Real Time Wildfire Monitoring

2020 ◽  
Vol 69 (5) ◽  
pp. 706-718
Author(s):  
Sangho Choe ◽  
Jeong-Hwa Yoo ◽  
Ponsuge Surani Shalika Tissera ◽  
Jo-In Kang ◽  
Hee-Kyung Yang
Keyword(s):  
Wireless Sensor Network ◽  
Low Power ◽  
Real Time ◽  
Sensor Network ◽  
Low Cost ◽  
Wireless Sensor ◽  
Event Processing

scholarly journals Low power GPS drifters with local storage and GSM modem made from off the shelf components

2019 ◽  
Author(s):  
Rolf Hut ◽  
Thanda Thatoe Nwe Win ◽  
Thom Bogaard
Keyword(s):  
Software Engineering ◽  
Low Power ◽  
Real Time ◽  
Low Cost ◽  
Gps Receivers ◽  
Open Hardware ◽  
Hydrodynamic Behaviour ◽  
Extensive Training ◽  
Hardware Component ◽  
Local Storage

Abstract. Drifters that track their position are important tools in studying the hydrodynamic behaviour of rivers. Drifters that can be tracked in real time have so far been rather expensive. Recently both GPS receivers and GSM modems have become available at lower prices to tinkering scientists due to the rise of the Open Hardware revolution and the associated Arduino ecosystem. This article serves two goals. Firstly, we provide detailed instructions on how to build a Low Power GPS drifter with local storage and GSM model that we tested in a fieldwork on the confluence of the Chindwin and Ayeyarwady rivers in Myanmar. These instructions allow fellow geoscientists to recreate the device. Secondly, we set the question: "Has the Open Hardware revolution progressed to the point that a low power GPS drifter that wireless transmits its position can be made from Open Hardware component by geoscientists without extensive training or expertise in electrical and software engineering? We feel this question is relevant and timely as more low-cost Open Hardware devices are promoted but in practice applicability often is restricted to the 'tinkering engineer'. We argue that because of the plug and play nature of the components geoscientist should be able to construct these type of devices. However, to get such devices to operate at low power levels that fieldwork often requires detailed (mircro)electrical expertise.

Multipurpose IoT network watchdog device with capability of add on sensors for multi instrument field stations.

2020 ◽  
Author(s):  
Panagiotis Argyrakis ◽  
Theodore Chinis ◽  
Alexandra Moshou ◽  
Nikolaos Sagias
Keyword(s):  
Real Time ◽  
Humidity Sensor ◽  
Low Cost ◽  
Mobile App ◽  
Severe Damage ◽  
Time Data ◽  
Data Gaps ◽  
Real Time Visualization ◽  
3D Printed ◽  
Excess Humidity

<p>Several stations (seismological, geodetical, etc.) suffer from communications problems, such problems create data gaps in real-time data transmission, also excess humidity and temperatures further than manufacturer limits, usually make components and circuitry, of expensive instruments, failure, and results to unaffordable service or unrepairable damage.</p><p>We create a low-cost opensource device that will raise the reliability of the stations and secure the instruments from severe damage, such a device installed as prototype at UOA (University of Athens) seismological station KARY (Karistos Greece) for a year and the reliability of the station raised tremendously, since then the device upgraded to provide wireless connection and IoT GUI (mobile app). A local server was built to serve all the devices uninterrupted and provide a secured network.</p><p>The software is fully customizable and multiple inputs can provide addon sensors capability, for example, gas sensor, humidity sensor, etc., all the data are collected to a remote database for real-time visualization and archiving for further analysis.</p><p>The shell which covers the circuitry is 3D-printed with a high temperature and humidity-resistant material and it’s also fully customizable by the user. </p>

A method for real-time error detection in low-cost environmental sensors data

2019 ◽  
Vol 8 (4) ◽  
pp. 338-350
Author(s):  
Mauricio Loyola
Keyword(s):  
Real Time ◽  
Error Detection ◽  
Measurement Errors ◽  
Low Cost ◽  
Detection Algorithm ◽  
Environmental Sensors ◽  
Content Type ◽  
Building Monitoring ◽  
Learning Techniques

Purpose The purpose of this paper is to propose a simple, fast, and effective method for detecting measurement errors in data collected with low-cost environmental sensors typically used in building monitoring, evaluation, and automation applications. Design/methodology/approach The method combines two unsupervised learning techniques: a distance-based anomaly detection algorithm analyzing temporal patterns in data, and a density-based algorithm comparing data across different spatially related sensors. Findings Results of tests using 60,000 observations of temperature and humidity collected from 20 sensors during three weeks show that the method effectively identified measurement errors and was not affected by valid unusual events. Precision, recall, and accuracy were 0.999 or higher for all cases tested. Originality/value The method is simple to implement, computationally inexpensive, and fast enough to be used in real-time with modest open-source microprocessors and a wide variety of environmental sensors. It is a robust and convenient approach for overcoming the hardware constraints of low-cost sensors, allowing users to improve the quality of collected data at almost no additional cost and effort.

scholarly journals Low-Cost Distributed Acoustic Sensor Network for Real-Time Urban Sound Monitoring

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2119
Author(s):  
Ester Vidaña-Vila ◽  
Joan Navarro ◽  
Cristina Borda-Fortuny ◽  
Dan Stowell ◽  
Rosa Ma Alsina-Pagès
Keyword(s):  
Real Time ◽  
Sensor Network ◽  
Large Scale ◽  
Learning Algorithm ◽  
Low Cost ◽  
Individual Performance ◽  
Sound Recognition ◽  
Continuous Exposure ◽  
Acoustic Sensor ◽  
Deep Learning Algorithm

Continuous exposure to urban noise has been found to be one of the major threats to citizens’ health. In this regard, several organizations are devoting huge efforts to designing new in-field systems to identify the acoustic sources of these threats to protect those citizens at risk. Typically, these prototype systems are composed of expensive components that limit their large-scale deployment and thus reduce the scope of their measurements. This paper aims to present a highly scalable low-cost distributed infrastructure that features a ubiquitous acoustic sensor network to monitor urban sounds. It takes advantage of (1) low-cost microphones deployed in a redundant topology to improve their individual performance when identifying the sound source, (2) a deep-learning algorithm for sound recognition, (3) a distributed data-processing middleware to reach consensus on the sound identification, and (4) a custom planar antenna with an almost isotropic radiation pattern for the proper node communication. This enables practitioners to acoustically populate urban spaces and provide a reliable view of noises occurring in real time. The city of Barcelona (Spain) and the UrbanSound8K dataset have been selected to analytically validate the proposed approach. Results obtained in laboratory tests endorse the feasibility of this proposal.

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