{"title":"A Fuzzy-Logic Based Adaptive Data Rate Scheme for Energy-Efficient LoRaWAN Communication","authors":"Rachel Kufakunesu, G. Hancke, A. Abu-Mahfouz","doi":"10.3390/jsan11040065","DOIUrl":"https://doi.org/10.3390/jsan11040065","url":null,"abstract":"Long Range Wide Area Network (LoRaWAN) technology is rapidly expanding as a technology with long distance connectivity, low power consumption, low data rates and a large number of end devices (EDs) that connect to the Internet of Things (IoT) network. Due to the heterogeneity of several applications with varying Quality of Service (QoS) requirements, energy is expended as the EDs communicate with applications. The LoRaWAN Adaptive Data Rate (ADR) manages the resource allocation to optimize energy efficiency. The performance of the ADR algorithm gradually deteriorates in dense networks and efforts have been made in various studies to improve the algorithm’s performance. In this paper, we propose a fuzzy-logic based adaptive data rate (FL-ADR) scheme for energy efficient LoRaWAN communication. The scheme is implemented on the network server (NS), which receives sensor data from the EDs via the gateway (GW) node and computes network parameters (such as the spreading factor and transmission power) to optimize the energy consumption of the EDs in the network. The performance of the algorithm is evaluated in ns-3 using a multi-gateway LoRa network with EDs sending data packets at various intervals. Our simulation results are analyzed and compared to the traditional ADR and the ns-3 ADR. The proposed FL-ADR outperforms the traditional ADR algorithm and the ns-3 ADR minimizing the interference rate and energy consumption.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116497388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Underwater Wireless Sensor Network Performance Analysis Using Diverse Routing Protocols","authors":"K. Sathish, C. Ravikumar, A. Rajesh, G. Pau","doi":"10.3390/jsan11040064","DOIUrl":"https://doi.org/10.3390/jsan11040064","url":null,"abstract":"The planet is the most water-rich place because the oceans cover more than 75% of its land area. Because of the unique activities that occur in the depths, we know very little about oceans. Underwater wireless sensors are tools that can continuously transmit data to one of the source sensors while monitoring and recording their surroundings’ physical and environmental parameters. An Underwater Wireless Sensor Network (UWSN) is the name given to the network created by collecting these underwater wireless sensors. This particular technology has a random path loss model due to the time-varying nature of channel parameters. Data transmission between underwater wireless sensor nodes requires a careful selection of routing protocols. By changing the number of nodes in the model and the maximum speed of each node, performance parameters, such as average transmission delay, average jitter, percentage of utilization, and power used in transmit and receive modes, are explored. This paper focuses on UWSN performance analysis, comparing various routing protocols. A network path using the source-tree adaptive routing-least overhead routing approach (STAR-LORA) Protocol exhibits 85.3% lower jitter than conventional routing protocols. Interestingly, the fisheye routing protocol achieves a 91.4% higher utilization percentage than its counterparts. The results obtained using the QualNet 7.1 simulator suggest the suitability of routing protocols in UWSN.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116143956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shruti Patil, Varadarajan Vijayakumar, Supriya Mahadevkar, Rohan Athawade, Lakhan Maheshwari, Shrushti Kumbhare, Yash Garg, Deepak S. Dharrao, P. Kamat, K. Kotecha
{"title":"Enhancing Optical Character Recognition on Images with Mixed Text Using Semantic Segmentation","authors":"Shruti Patil, Varadarajan Vijayakumar, Supriya Mahadevkar, Rohan Athawade, Lakhan Maheshwari, Shrushti Kumbhare, Yash Garg, Deepak S. Dharrao, P. Kamat, K. Kotecha","doi":"10.3390/jsan11040063","DOIUrl":"https://doi.org/10.3390/jsan11040063","url":null,"abstract":"Optical Character Recognition has made large strides in the field of recognizing printed and properly formatted text. However, the effort attributed to developing systems that are able to reliably apply OCR to both printed as well as handwritten text simultaneously, such as hand-filled forms, is lackadaisical. As Machine printed/typed text follows specific formats and fonts while handwritten texts are variable and non-uniform, it is very hard to classify and recognize using traditional OCR only. A pre-processing methodology employing semantic segmentation to identify, segment and crop boxes containing relevant text on a given image in order to improve the results of conventional online-available OCR engines is proposed here. In this paper, the authors have also provided a comparison of popular OCR engines like Microsoft Cognitive Services, Google Cloud Vision and AWS recognitions. We have proposed a pixel-wise classification technique to accurately identify the area of an image containing relevant text, to feed them to a conventional OCR engine in the hopes of improving the quality of the output. The proposed methodology also supports the digitization of mixed typed text documents with amended performance. The experimental study shows that the proposed pipeline architecture provides reliable and quality inputs through complex image preprocessing to Conventional OCR, which results in better accuracy and improved performance.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121085595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Irrai Anbu Jayaraj, Bharanidharan Shanmugam, S. Azam, Ganthan Narayana Samy
{"title":"A Systematic Review of Radio Frequency Threats in IoMT","authors":"Irrai Anbu Jayaraj, Bharanidharan Shanmugam, S. Azam, Ganthan Narayana Samy","doi":"10.3390/jsan11040062","DOIUrl":"https://doi.org/10.3390/jsan11040062","url":null,"abstract":"In evolving technology, attacks on medical devices are optimized due to the driving force of AI, computer vision, mixed reality, and the internet of things (IoT). Optimizing cybersecurity on the internet of medical things (IoMT) and building cyber resiliency against crime-as-a-service (CaaS) in the healthcare ecosystem are challenging due to various attacks, including spectrum-level threats at the physical layer. Therefore, we conducted a systematic literature review to identify the research gaps and propose potential solutions to spectrum threats on IoMT devices. The purpose of this study is to provide an overview of the literature on wireless spectrum attacks. The papers we reviewed covered cyber impacts, layered attacks, attacks on protocols, sniffing attacks, field experimentation with cybersecurity testbeds, radiofrequency machine learning, and data collection. In the final section, we discuss future directions, including the sniffing attack mitigation framework in IoMT devices operating under a machine implantable communication system (MICS). To analyze the research papers about physical attacks against IoT in health care, we followed the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines. Scopus, PubMed, and Web of Science were searched for peer-reviewed articles, and we conducted a thorough search using these resources. The search on Scopus containing the terms “jamming attack” and “health” yielded 330 rows, and the investigation on WoS yielded 17 rows. The search terms “replay attack” and “health” yielded 372 rows in Scopus, while PubMed yielded 23 rows, and WoS yielded 50 articles. The search terms “side-channel attack” and “health” yielded 447 rows in Scopus, WoS yielded 30 articles, and the search terms “sniffing attack” and “health” yielded 18 rows in Scopus, while PubMed yielded 1 row, and WoS yielded 0 articles. The terms “spoofing attack” and “health” yielded 316 rows in Scopus, while PubMed yielded 5 rows, and WoS yielded 23 articles. Finally, the search terms “tampering attack” and “health” yielded 25 rows in Scopus, PubMed yielded 14 rows, and WoS yielded 46 rows. The search time frame was from 2003 to June 2022. The findings show a research gap in sniffing, tampering, and replay attacks on the IoMT. We have listed the items that were included and excluded and provided a detailed summary of SLR. A thorough analysis of potential gaps has been identified, and the results are visualized for ease of understanding.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"28 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113975138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Improving the Performance of Opportunistic Networks in Real-World Applications Using Machine Learning Techniques","authors":"Samaneh Rashidibajgan, Thomas Hupperich","doi":"10.3390/jsan11040061","DOIUrl":"https://doi.org/10.3390/jsan11040061","url":null,"abstract":"In Opportunistic Networks, portable devices such as smartphones, tablets, and wearables carried by individuals, can communicate and save-carry-forward their messages. The message transmission is often in the short range supported by communication protocols, such as Bluetooth, Bluetooth Low Energy, and Zigbee. These devices carried by individuals along with a city’s taxis and buses represent network nodes. The mobility, buffer size, message interval, number of nodes, and number of messages copied in such a network influence the network’s performance. Extending these factors can improve the delivery of the messages and, consequently, network performance; however, due to the limited network resources, it increases the cost and appends the network overhead. The network delivers the maximized performance when supported by the optimal factors. In this paper, we measured, predicted, and analyzed the impact of these factors on network performance using the Opportunistic Network Environment simulator and machine learning techniques. We calculated the optimal factors depending on the network features. We have used three datasets, each with features and characteristics reflecting different network structures. We collected the real-time GPS coordinates of 500 taxis in San Francisco, 320 taxis in Rome, and 196 public transportation buses in Münster, Germany, within 48 h. We also compared the network performance without selfish nodes and with 5%, 10%, 20%, and 50% selfish nodes. We suggested the optimized configuration under real-world conditions when resources are limited. In addition, we compared the performance of Epidemic, Prophet, and PPHB++ routing algorithms fed with the optimized factors. The results show how to consider the best settings for the network according to the needs and how self-sustaining nodes will affect network performance.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132195772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abhishek Sharma, Sushank Chaudhary, J. Malhotra, Sunita Khichar, L. Wuttisittikulkij
{"title":"Photonic Sensor for Multiple Targets Detection under Adverse Weather Conditions in Autonomous Vehicles","authors":"Abhishek Sharma, Sushank Chaudhary, J. Malhotra, Sunita Khichar, L. Wuttisittikulkij","doi":"10.3390/jsan11040060","DOIUrl":"https://doi.org/10.3390/jsan11040060","url":null,"abstract":"Detection and tracing of multiple targets in a real-time scenario, particularly in the urban setup under adverse atmospheric conditions, has become a major challenge for autonomous vehicles (AVs). Photonic radars have emerged as promising candidates for Avs to realize via the recognition of traffic patterns, navigation, lane detection, self-parking, etc. In this work we developed a direct detection-based, frequency-modulated photonic radar to detect multiple stationary targets using four different transmission channels multiplexed over a single free space channel via wavelength division multiplexing (WDM). Additionally, the performance of the proposed photonic radar was examined under the impact of adverse weather conditions, such as rain and fog. The reported results in terms of received power and signal-to-noise ratio (SNR) showed successful detection of all the targets with bandwidths of 1 GHz and 4 GHz. The proposed system was also tested for range resolution of targets at 150 m and 6.75 cm resolution with 4 GHz bandwidth was reported, while resolution of 50 cm was reported with 1 GHz of bandwidth.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126672055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Smart City: The Different Uses of IoT Sensors","authors":"G. Pau, Fabio Arena","doi":"10.3390/jsan11040058","DOIUrl":"https://doi.org/10.3390/jsan11040058","url":null,"abstract":"We refer to an interconnected city with shared intelligence when discussing Smart City and Internet of Things (IoT) sensors—a city governed in real time thanks to the recently gained ability to gather data through thousands of deployed sensors [...]","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134030211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mobile Edge Computing in Space-Air-Ground Integrated Networks: Architectures, Key Technologies and Challenges","authors":"Yuan Qiu, Jianwei Niu, Xinzhong Zhu, Kuntuo Zhu, Yiming Yao, Beibei Ren, Tao Ren","doi":"10.3390/jsan11040057","DOIUrl":"https://doi.org/10.3390/jsan11040057","url":null,"abstract":"Space-air-ground integrated networks (SAGIN) provide seamless global coverage and cross-domain interconnection for the ubiquitous users in heterogeneous networks, which greatly promote the rapid development of intelligent mobile devices and applications. However, for mobile devices with limited computation capability and energy budgets, it is still a serious challenge to meet the stringent delay and energy requirements of computation-intensive ubiquitous mobile applications. Therefore, in view of the significant success in ground mobile networks, the introduction of mobile edge computing (MEC) in SAGIN has become a promising technology to solve the challenge. By deploying computing, cache, and communication resources in the edge of mobile networks, SAGIN MEC provides both low latency, high bandwidth, and wide coverage, substantially improving the quality of services for mobile applications. There are still many unprecedented challenges, due to its high dynamic, heterogeneous and complex time-varying topology. Therefore, efficient MEC deployment, resource management, and scheduling optimization in SAGIN are of great significance. However, most existing surveys only focus on either the network architecture and system model, or the analysis of specific technologies of computation offloading, without a complete description of the key MEC technologies for SAGIN. Motivated by this, this paper first presents a SAGIN network system architecture and service framework, followed by the descriptions of its characteristics and advantages. Then, the MEC deployment, network resources, edge intelligence, optimization objectives and key algorithms in SAGIN are discussed in detail. Finally, potential problems and challenges of MEC in SAGIN are discussed for future work.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130486752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Perception Enhancement and Improving Driving Context Recognition of an Autonomous Vehicle Using UAVs","authors":"Abderraouf Khezaz, M. D. Hina, A. Ramdane-Cherif","doi":"10.3390/jsan11040056","DOIUrl":"https://doi.org/10.3390/jsan11040056","url":null,"abstract":"The safety of various road users and vehicle passengers is very important in our increasingly populated roads and highways. To this end, the correct perception of driving conditions is imperative for a driver to react accordingly to a given driving situation. Various sensors are currently being used in recognizing driving context. To further enhance such driving environment perception, this paper proposes the use of UAVs (unmanned aerial vehicles, also known as drones). In this work, drones are equipped with sensors (radar, lidar, camera, etc.), capable of detecting obstacles, accidents, and the like. Due to their small size and capability to move places, drones can be used collect perception data and transmit them to the vehicle using a secure method, such as an RF, VLC, or hybrid communication protocol. These data obtained from different sources are then combined and processed using a knowledge base and some set of logical rules. The knowledge base is represented by ontology; it contains various logical rules related to the weather, the appropriateness of sensors with respect to the weather, and the activation mechanism of UAVs containing these sensors. Logical rules about which communication protocols to use also exist. Finally, various driving context cognition rules are provided. The result is a more reliable environment perception for the vehicle. When necessary, users are provided with driving assistance information, leading to safe driving and fewer road accidents. As a proof of concept, various use cases were tested in a driving simulator in the laboratory. Experimental results show that the system is an effective tool in improving driving context recognition and in preventing road accidents.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128647666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Z. Abduljabbar, V. O. Nyangaresi, M. A. A. Sibahee, M. J. J. Ghrabat, Junchao Ma, I. Q. Abduljaleel, Abdulla J. Y. Aldarwish
{"title":"Session-Dependent Token-Based Payload Enciphering Scheme for Integrity Enhancements in Wireless Networks","authors":"Z. Abduljabbar, V. O. Nyangaresi, M. A. A. Sibahee, M. J. J. Ghrabat, Junchao Ma, I. Q. Abduljaleel, Abdulla J. Y. Aldarwish","doi":"10.3390/jsan11030055","DOIUrl":"https://doi.org/10.3390/jsan11030055","url":null,"abstract":"Wireless networks have continued to evolve to offer connectivity between users and smart devices such as drones and wireless sensor nodes. In this environment, insecure public channels are deployed to link the users to their remote smart devices. Some of the application areas of these smart devices include military surveillance and healthcare monitoring. Since the data collected and transmitted to the users are highly sensitive and private, any leakages can have adverse effects. As such, strong entity authentication should be implemented before any access is granted in these wireless networks. Although numerous protocols have been developed for this purpose, the simultaneous attainment of robust security and privacy at low latencies, execution time and bandwidth remains a mirage. In this paper, a session-dependent token-based payload enciphering scheme for integrity enhancements in wireless networks is presented. This protocol amalgamates fuzzy extraction with extended Chebyshev chaotic maps to boost the integrity of the exchanged payload. The security analysis shows that this scheme offers entity anonymity and backward and forward key secrecy. In addition, it is demonstrated to be robust against secret ephemeral leakage, side-channeling, man-in-the-middle and impersonation attacks, among other security threats. From the performance perspective, the proposed scheme requires the least communication overheads and a relatively low execution time during the authentication process.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122716938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}