scholarly journals RSS-Based Localization and Mobility Evaluation Using a Single NB-IoT Cell

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6172
Author(s):  
Thomas Janssen ◽  
Rafael Berkvens ◽  
Maarten Weyn
Keyword(s):  
Low Power ◽  
Large Scale ◽  
Low Cost ◽  
Estimation Error ◽  
Signal Strength ◽  
Location Estimation ◽  
Wide Area Networks ◽  
Localization Performance ◽  
Cell Reselection ◽  
Signals Of Opportunity

Low Power Wide Area Networks (LPWAN) have the ability to localize a mobile transmitter using signals of opportunity, as a low power and low cost alternative to satellite-based solutions. In this paper, we evaluate the accuracy of three localization approaches based on the Received Signal Strength (RSS). More specifically, the performance of a proximity, range-based and optimized fingerprint-based algorithm is evaluated in a large-scale urban environment using a public Narrowband Internet of Things (NB-IoT) network. The results show a mean location estimation error of 340, 320 and 204 m, respectively. During the measurement campaign, we discovered a mobility issue in NB-IoT. In contrast to other LPWAN and cellular technologies which use multiple gateways or cells to locate a device, only a single cell antenna can be used for RSS-based localization in NB-IoT. Therefore, we address this limitation in the current NB-IoT hardware and software by studying the mobility of the cellular-based 3GPP standard in a localization context. Experimental results show that the lack of handover support leads to increased cell reselection time and poor cell sector reliability, which in turn results in reduced localization performance.

scholarly journals Experimental Study of LoRa Transmission over Seawater

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2853 ◽  
Author(s):  
Nikola Jovalekic ◽  
Vujo Drndarevic ◽  
Ermanno Pietrosemoli ◽  
Iain Zennaro
Keyword(s):  
Field Experiments ◽  
Low Cost ◽  
Signal Strength ◽  
Wide Area Networks ◽  
Receive Signal Strength Indicator ◽  
Correction Factors ◽  
Wide Range ◽  
Actual Signal ◽  
Path Condition ◽  
Clear Line

Low Power Wide Area Networks (LPWANs) are gaining attention in both academia and industry by offering the possibility of connecting a large number of nodes over extended distances. LoRa is one of the technologies used as a physical layer in such networks. This paper investigates the LoRa links over seawater in two typical scenarios: clear Line-of-Sight (LOS) and obstructed path in two different Industrial, Scientific and Medical (ISM) radio bands: 868 MHz and 434 MHz. We used three different LoRa devices in the experiments: the Own Developed LoRa Transceiver (ODT) and two commercial transceivers. Firstly we investigated transceivers’ Receive Signal Strength Indicator (RSSI) and Signal-to-Noise (SNR) measurement chain linearity and provided correction factors for RSSI to correlate it with actual signal levels received at transceivers’ inputs. Next, we carried out field experiments for three different LoRa Spreading Factors, S F ∈ [ 7 , 10 , 12 ] , within a bandwidth of B W = 125 kHz and Coding Rate C R = 4 / 6 . The experiments showed that LoRa links are fully feasible over seawater at distances at least 22 km long, using only low-cost off-the-shelf rubber duck antennas in LOS path condition in both ISM bands. In addition, we showed that LoRa links can be established over 28 km obstructed LOS oversea path in ISM 434 MHz band, but using costly, higher gain antennas. Furthermore, the laboratory experiments revealed that RSSI is linear in a wide range, up to - 50 dBm, whereas the SNR measurement chain goes into saturation for Received Signal Strength (RSS) values higher than - 100 dBm. These findings enabled accurate interpretation of the results obtained in field experiments.

scholarly journals A Practical Load Disaggregation Approach for Monitoring Industrial Users Demand with Limited Data Availability

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4880
Author(s):  
Sara Tavakoli ◽  
Kaveh Khalilpour
Keyword(s):  
Large Scale ◽  
Service Providers ◽  
Low Cost ◽  
Estimation Error ◽  
Data Availability ◽  
Smart Meters ◽  
Industrial Sectors ◽  
Load Monitoring ◽  
Load Disaggregation ◽  
Electrical Loads

The emergence of smart sensors has had a significant impact on the utility industry. In particular, it has made the planning and implementation of demand-side management (DSM) programmes easier. Nevertheless, for various reasons, some users may not implement smart meters for load monitoring. This paper addresses such cases, particularly large-scale industrial users, which, despite heavy electrical loads coming from many different processes, implement only simple energy measuring equipment for billing purposes. This necessitates the utilisation of novel methodologies for load disaggregation, often referred to as nonintrusive load monitoring (NILM). The availability of such tools can create multifold benefits for industrial park management, utility service providers, regulators, and policymakers. Here, we introduce an optimisation algorithm for nonintrusive load disaggregation that is low-cost, speedy, and acceptably accurate. As a case study, we used real network data of three industrial sectors: food processing, stonecutting, and glassmaking. For all cases, the optimisation framework developed a desegregated profile and estimated the load with an error of less than 5%. For non-workdays, given the higher uncertainty for the continuity of different processes, the estimation error was higher but still in an acceptable range of around 3.63–15.09% with an average of 8.10%.

LoRaWAN for an IoT-based environmental monitoring application in Tirana city

2021 ◽  
Author(s):  
Evjola Spaho ◽  
Aleksandër Biberaj ◽  
Ares Tahiraga
Keyword(s):  
Low Power ◽  
Environmental Monitoring ◽  
Long Range ◽  
Low Cost ◽  
Wide Area ◽  
Wide Area Networks ◽  
Area Network ◽  
Wide Area Network ◽  
Long Distance ◽  
Monitoring Application

AbstractRecently, low power wide area networks are attracting a lot of attention by the research community. They are wireless technologies characterized by large coverage area, low bandwidth and long battery life. One of these low power wide area networks technologies, the long range wide area network, can be used for different monitoring applications for health, agriculture, traffic, smart city.In this paper, different simulations and experiments are conducted to implement a low-cost long-range wide area network environmental monitoring application for Tirana city in Albania. Simulation and experimental data are compared and similar results were obtained. In the low-cost implemented system, the gateway can communicate with the sensors placed in strategic positions with long distance covered also using Radio Mobile software.

Progress in Microbial Fuel Cells Energy Production

2011 ◽  
Vol 324 ◽  
pp. 457-460 ◽  
Author(s):  
Nicolas Degrenne ◽  
Francois Buret ◽  
Bruno Allard ◽  
Jean Michel Monier
Keyword(s):  
Organic Matter ◽  
Fuel Cells ◽  
Low Power ◽  
Microbial Fuel Cells ◽  
Energy Production ◽  
Large Scale ◽  
Low Cost ◽  
Electrical Power ◽  
Payback Time ◽  
Power Densities

Microbial fuel cells (MFCs) harness the natural metabolisms of microbes to produce electrical power from almost any kind of organic matter. In addition to the low power densities (about 1mW for a 1-liter reactor), MFCs are presently built with expensive membrane and electrodes. The payback time of MFCs is therefore very long (evaluated to 25000 years for our lab prototype). Progresses in designing low-cost MFCs are necessary before conceiving large scale energy production.

scholarly journals IMPROVED INDOOR LOCALIZATION WITH DIVERSITY AND FILTERING BASED ON RECEIVED SIGNAL STRENGTH MEASUREMENTS

2010 ◽  
pp. 9-15
Author(s):  
Andreas Fink ◽  
Helmut Beikirch ◽  
Matthias Voss
Keyword(s):  
Data Transmission ◽  
Indoor Localization ◽  
Estimation Error ◽  
Path Loss ◽  
Distance Estimation ◽  
Signal Strength ◽  
Location Estimation ◽  
Indoor Environments ◽  
Redundant Data ◽  
Unknown Node

Distance estimation by the evaluation of RSSI measurements is a simple and well-known technique to predict the position of an unknown node. Therefore the infrastructure does not have to be extended by expensive hardware for synchronization or direction approximation. However, with the localization based on RSSI measurements common and proven systems can be used for the infrastructure. For indoor environments the distance-pending path loss is affected by strong variations, especially appearing as frequency specific signal dropouts. A diversity concept with redundant data transmission in different frequency bands can reduce the dropout probability. If also space diversity and plausibility filtering are used, the Location Estimation Error can be reduced significantly. The investigations show that a good performance for precision and availability can also be reached with low infrastructural costs.

scholarly journals Sigfox and LoRaWAN Datasets for Fingerprint Localization in Large Urban and Rural Areas

2018 ◽  
Author(s):  
Michiel Aernouts ◽  
Rafael Berkvens ◽  
Koen Van Vlaenderen ◽  
Maarten Weyn
Keyword(s):  
Rural Areas ◽  
Large Scale ◽  
Estimation Error ◽  
Location Estimation ◽  
Location Based Services ◽  
Area Network ◽  
Wide Area Network ◽  
Location Data ◽  
Outdoor Environments ◽  
Urban And Rural Areas

Because of the increasing relevance of the Internet of Things and location-based services, researchers are evaluating wireless positioning techniques, such as fingerprinting, on Low Power Wide Area Network (LPWAN) communication. In order to evaluate fingerprinting in large outdoor environments, extensive, time-consuming measurement campaigns need to be conducted to create useful datasets. This paper presents three LPWAN datasets which are collected in large-scale urban and rural areas. The goal is to provide the research community with a tool to evaluate fingerprinting algorithms in large outdoor environments. During a period of three months, numerous mobile devices periodically obtained location data via a GPS receiver which was transmitted via a Sigfox or LoRaWAN message. Together with network information, this location data is stored in the appropriate LPWAN dataset. The first results of our basic fingerprinting implementation, which is also clarified in this paper, indicate a mean location estimation error of 214.58 m for the rural Sigfox dataset, 688.97 m for the urban Sigfox dataset and 398.40 m for the urban LoRaWAN dataset. In the future, we will enlarge our current datasets and use them to evaluate and optimize our fingerprinting methods. Also, we intend to collect additional datasets for Sigfox, LoRaWAN and NB-IoT.

scholarly journals Advances in Optical Based Turbidity Sensing Using LED Photometry (PEDD)

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 254
Author(s):  
Cormac D. Fay ◽  
Andrew Nattestad
Keyword(s):  
Water Quality ◽  
Low Power ◽  
Spectral Sensitivity ◽  
Large Scale ◽  
Limit Of Detection ◽  
Low Cost ◽  
Environmental Concerns ◽  
Sensitivity Limit ◽  
Calibration Standards ◽  
Detector Diode

Turbidity is one of the primary metrics to determine water quality in terms of health and environmental concerns, however analysis typically takes place in centralized facilities, with samples periodically collected and transported there. Large scale autonomous deployments (WSNs) are impeded by both initial and per measurement costs. In this study we employ a Paired Emitter-Detector Diode (PEDD) technique to quantitatively measure turbidity using analytical grade calibration standards. Our PEDD approach compares favorably against more conventional photodiode-LED arrangements in terms of spectral sensitivity, cost, power use, sensitivity, limit of detection, and physical arrangement as per the ISO 7027 turbidity sensing standard. The findings show that the PEDD technique was superior in all aforementioned aspects. It is therefore more ideal for low-cost, low-power, IoT deployed sensors. The significance of these findings can lead to environmental deployments that greatly lower the device and per-measurement costs.

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