scholarly journals Low-Power Failure Detection for Environmental Monitoring Based on IoT

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6489
Author(s):  
Jiaxi Liu ◽  
Weizhong Gao ◽  
Jian Dong ◽  
Na Wu ◽  
Fei Ding
Keyword(s):  
Low Power ◽  
Environmental Monitoring ◽  
Failure Detection ◽  
Node Failure ◽  
Detection Algorithms ◽  
Software Failure ◽  
Power Failure ◽  
Battery Consumption ◽  
Speed Accuracy ◽  
The Internet Of Things

Many environmental monitoring applications that are based on the Internet of Things (IoT) require robust and available systems. These systems must be able to tolerate the hardware or software failure of nodes and communication failure between nodes. However, node failure is inevitable due to environmental and human factors, and battery depletion in particular is a major contributor to node failure. The existing failure detection algorithms seldom consider the problem of node battery consumption. In order to rectify this, we propose a low-power failure detector (LP-FD) that can provide an acceptable failure detection service and can save on the battery consumption of nodes. From simulation experiments, results show that the LP-FD can provide better detection speed, accuracy, overhead and battery consumption than other failure detection algorithms.

scholarly journals A Complete Key Management Scheme for LoRaWAN v1.1

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2962
Author(s):  
Xingda Chen ◽  
Margaret Lech ◽  
Liuping Wang
Keyword(s):  
Low Power ◽  
Key Management ◽  
Wide Area Networks ◽  
Key Generation ◽  
Security Framework ◽  
Data Confidentiality ◽  
Backward Compatibility ◽  
Management Scheme ◽  
The Internet Of Things ◽  
Key Management Scheme

Security is one of the major concerns of the Internet of Things (IoT) wireless technologies. LoRaWAN is one of the emerging Low Power Wide Area Networks being developed for IoT applications. The latest LoRaWAN release v.1.1 has provided a security framework that includes data confidentiality protection, data integrity check, device authentication and key management. However, its key management part is only ambiguously defined. In this paper, a complete key management scheme is proposed for LoRaWAN. The scheme addresses key updating, key generation, key backup, and key backward compatibility. The proposed scheme was shown not only to enhance the current LoRaWAN standard, but also to meet the primary design consideration of LoRaWAN, i.e., low power consumption.

scholarly journals Energy Efficiency in Short and Wide-Area IoT Technologies—A Survey

Technologies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 22
Author(s):  
Eljona Zanaj ◽  
Giuseppe Caso ◽  
Luca De Nardis ◽  
Alireza Mohammadpour ◽  
Özgü Alay ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Low Power ◽  
Energy Efficient ◽  
Wide Area ◽  
Wide Area Networks ◽  
The Internet ◽  
Extensive Review ◽  
Research Directions ◽  
The Internet Of Things

In the last years, the Internet of Things (IoT) has emerged as a key application context in the design and evolution of technologies in the transition toward a 5G ecosystem. More and more IoT technologies have entered the market and represent important enablers in the deployment of networks of interconnected devices. As network and spatial device densities grow, energy efficiency and consumption are becoming an important aspect in analyzing the performance and suitability of different technologies. In this framework, this survey presents an extensive review of IoT technologies, including both Low-Power Short-Area Networks (LPSANs) and Low-Power Wide-Area Networks (LPWANs), from the perspective of energy efficiency and power consumption. Existing consumption models and energy efficiency mechanisms are categorized, analyzed and discussed, in order to highlight the main trends proposed in literature and standards toward achieving energy-efficient IoT networks. Current limitations and open challenges are also discussed, aiming at highlighting new possible research directions.

Applying the Internet of Things into Ecological Environmental Monitoring

2012 ◽  
Vol 198-199 ◽  
pp. 1755-1760 ◽  
Author(s):  
Guo Ping Zhou ◽  
Ya Nan Chen
Keyword(s):  
Internet Of Things ◽  
Environmental Monitoring ◽  
Software Design ◽  
Ecological Environment ◽  
Future Research ◽  
The Internet ◽  
Environment Monitoring ◽  
Carbon Dioxide Gas ◽  
Data Collection And Analysis ◽  
The Internet Of Things

Applying the Internet of Things (IOT) into ecological environmental monitoring is the goal of this paper. There are several advantages of the Internet of Things (IOT) applying in ecological environment monitoring. A hierarchical monitoring system is presented, including system architecture, hardware/software design, information flow and software implementation. In the end, using carbon dioxide gas in the atmosphere for experimental purposes, in data collection and analysis. Experiments showed that this system is capable of monitoring ecologica environment, which orientate the future research of forest ecosystem.

scholarly journals Unsupervised Anomaly Detection with Distillated Teacher-Student Network Ensemble

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 201
Author(s):  
Qinfeng Xiao ◽  
Jing Wang ◽  
Youfang Lin ◽  
Wenbo Gongsa ◽  
Ganghui Hu ◽  
...  
Keyword(s):  
Anomaly Detection ◽  
Multivariate Data ◽  
Failure Detection ◽  
Superior Performance ◽  
Detection Algorithms ◽  
Teacher Student ◽  
Model Complex ◽  
Unsupervised Anomaly Detection ◽  
Real World Datasets ◽  
Complex Features

We address the problem of unsupervised anomaly detection for multivariate data. Traditional machine learning based anomaly detection algorithms rely on specific assumptions of normal patterns and fail to model complex feature interactions and relations. Recently, existing deep learning based methods are promising for extracting representations from complex features. These methods train an auxiliary task, e.g., reconstruction and prediction, on normal samples. They further assume that anomalies fail to perform well on the auxiliary task since they are never trained during the model optimization. However, the assumption does not always hold in practice. Deep models may also perform the auxiliary task well on anomalous samples, leading to the failure detection of anomalies. To effectively detect anomalies for multivariate data, this paper introduces a teacher-student distillation based framework Distillated Teacher-Student Network Ensemble (DTSNE). The paradigm of the teacher-student distillation is able to deal with high-dimensional complex features. In addition, an ensemble of student networks provides a better capability to avoid generalizing the auxiliary task performance on anomalous samples. To validate the effectiveness of our model, we conduct extensive experiments on real-world datasets. Experimental results show superior performance of DTSNE over competing methods. Analysis and discussion towards the behavior of our model are also provided in the experiment section.

scholarly journals Adaptive Data Synchronization Algorithm for IoT-Oriented Low-Power Wide-Area Networks

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4053 ◽  
Author(s):  
Andrea Petroni ◽  
Francesca Cuomo ◽  
Leonisio Schepis ◽  
Mauro Biagi ◽  
Marco Listanti ◽  
...  
Keyword(s):  
Low Power ◽  
Mobile Communications ◽  
Data Exchange ◽  
Energy Savings ◽  
Wide Area ◽  
Wide Area Networks ◽  
Battery Life ◽  
File Synchronization ◽  
The Internet Of Things

The Internet of Things (IoT) is by now very close to be realized, leading the world towards a new technological era where people’s lives and habits will be definitively revolutionized. Furthermore, the incoming 5G technology promises significant enhancements concerning the Quality of Service (QoS) in mobile communications. Having billions of devices simultaneously connected has opened new challenges about network management and data exchange rules that need to be tailored to the characteristics of the considered scenario. A large part of the IoT market is pointing to Low-Power Wide-Area Networks (LPWANs) representing the infrastructure for several applications having energy saving as a mandatory goal besides other aspects of QoS. In this context, we propose a low-power IoT-oriented file synchronization protocol that, by dynamically optimizing the amount of data to be transferred, limits the device level of interaction within the network, therefore extending the battery life. This protocol can be adopted with different Layer 2 technologies and provides energy savings at the IoT device level that can be exploited by different applications.

scholarly journals Worldwide Connectivity for the Internet of Things Through LoRaWAN

2019 ◽  
Vol 11 (3) ◽  
pp. 57 ◽  
Author(s):  
Lorenzo Vangelista ◽  
Marco Centenaro
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Cellular Network ◽  
Wide Area ◽  
The Internet ◽  
Area Network ◽  
Wide Area Network ◽  
Frequency Bands ◽  
The Moment ◽  
The Internet Of Things

The low-power wide-area network (LPWAN) paradigm is gradually gaining market acceptance. In particular, three prominent LPWAN technologies are emerging at the moment: LoRaWAN™ and SigFox™, which operate on unlicensed frequency bands, and NB-IoT, operating on licensed frequency bands. This paper deals with LoRaWAN™, and has the aim of describing a particularly interesting feature provided by the latest LoRaWAN™ specification—often neglected in the literature—i.e., the roaming capability between different operators of LoRaWAN™ networks, across the same country or even different countries. Recalling that LoRaWAN™ devices do not have a subscriber identification module (SIM) like cellular network terminals, at a first glance the implementation of roaming in LoRaWAN™ networks could seem intricate. The contribution of this paper consists in explaining the principles behind the implementation of a global LoRaWAN network, with particular focus on how to cope with the lack of the SIM in the architecture and how to realize roaming.

scholarly journals Sensor Node Failure Detection

2015 ◽  
Vol V4 (04) ◽  
Author(s):  
Grace John M ◽  
Anusha Chacko ◽  
Amresh Kumar ◽  
Aparna Gopinath P. K ◽  
Keyword(s):  
Sensor Node ◽  
Failure Detection ◽  
Node Failure
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