Journal of Sensor and Actuator Networks (ISSN 2224-2708) is an international open access journal on the science and technology of sensor and actuator networks. It publishes regular research papers, reviews (including comprehensive reviews on complete sensor and actuator networks), and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.

The Journal of Sensor and Actuator Networks is an international open access journal dedicated to the science and technology of sensor and actuator networks. It publishes regular research papers, reviews (including comprehensive reviews on complete sensor and actuator networks), and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There are no restrictions on the length of the papers, and full experimental details must be provided to ensure that the results can be reproduced.

《Journal of Sensor and Actuator Networks》是一本国际开放获取期刊，专注于传感器和执行器网络的科学与技术。期刊发表常规研究论文、综述（包括对完整传感器和执行器网络的综合评述）以及简短通讯。我们的目标是鼓励科学家尽可能详细地发布他们的实验和理论结果。对论文的长度没有限制，必须提供完整的实验细节，以便结果能够被复现。

Journal of Sensor and Actuator Networks

Bluetooth technology is a key component of wireless communications. It provides a low-energy and low-cost solution for short-range radio transmissions. Bluetooth, more specifically Bluetooth Low Energy (BLE) has become the predominant technology for connecting IoT (Internet of Things). It can be found in cell phones, headsets, speakers, printers, keyboards, automobiles, children’s toys, and medical devices, as well as many other devices. The technology can also be found in automated smart homes, to provide monitors and controls for lights, thermostats, door locks, appliances, security systems, and cameras. Bluetooth offers convenience and ease of use, but it lacks a centralized security infrastructure. As a result, it has serious security vulnerabilities, and the need for awareness of the security risks are increasing as the technology becomes more widespread. This paper presents an overview of Bluetooth technology in IoT including its security, vulnerabilities, threats, and risk mitigation solutions, as well as real-life examples of exploits. Our study highlights the importance of understanding attack risks and mitigation techniques involved with using Bluetooth technology on our devices. Real-life examples of recent Bluetooth exploits are presented. Several recommended security measures are discussed to secure Bluetooth communication.

Angela M. Lonzetta

Peter Cope

Joseph Campbell

Bassam J. Mohd

Thaier Hayajneh

Security Vulnerabilities in Bluetooth Technology as Used in IoT

物联网中蓝牙技术的安全漏洞

The smart ocean has been regarded as an integrated sensing, communication, and computing ecosystem developed for connecting marine objects in surface and underwater environments. The development of the smart ocean is expected to support a variety of marine applications and services such as resource exploration, marine disaster rescuing, and environment monitoring. However, the complex and dynamic marine environments and the limited network resources raise new challenges in marine communication and computing, especially for these computing-intensive and delay-sensitive tasks. Recently, the space–air–ground–sea integrated networks have been envisioned as a promising network framework to enhance the communication and computing performance. In this paper, we conduct a comprehensive survey on the integrated sensing, communication, and computing networks (ISCCNs) for smart oceans based on the collaboration of space–air–ground–sea networks from four domains (i.e., space layer, aerial layer, sea surface layer, and underwater layer), and five aspects (i.e., sensing-related, communication-related, computation-related, security-related, and application-related). Specifically, we provide the key technologies for the ISCCNs in smart oceans, and introduce the state-of-the-art marine sensing, communication, and computing paradigms. The emerging challenges with the potential solutions of the ISCCNs for smart oceans are illustrated to enable the intelligent services. Moreover, the new applications for the ISCCNs in smart oceans are discussed, and potential research directions in smart oceans are provided for future works.

Minghui Dai

Yang Li

Peichun Li

Yuan Wu

Liping Qian

Bin Lin

Zhou Su

JSAN

A Survey on Integrated Sensing, Communication, and Computing Networks for Smart Oceans

智能海洋综合感知、通信与计算网络综述

In recent times, distributed denial of service (DDoS) has been one of the most prevalent security threats in internet-enabled networks, with many internet of things (IoT) devices having been exploited to carry out attacks. Due to their inherent security flaws, the attacks seek to deplete the resources of the target network by flooding it with numerous spoofed requests from a distributed system. Research studies have demonstrated that a DDoS attack has a considerable impact on the target network resources and can result in an extended operational outage if not detected. The detection of DDoS attacks has been approached using a variety of methods. In this paper, a comprehensive survey of the methods used for DDoS attack detection on selected internet-enabled networks is presented. This survey aimed to provide a concise introductory reference for early researchers in the development and application of attack detection methodologies in IoT-based applications. Unlike other studies, a wide variety of methods, ranging from the traditional methods to machine and deep learning methods, were covered. These methods were classified based on their nature of operation, investigated as to their strengths and weaknesses, and then examined via several research studies which made use of each approach. In addition, attack scenarios and detection studies in emerging networks such as the internet of drones, routing protocol based IoT, and named data networking were also covered. Furthermore, technical challenges in each research study were identified. Finally, some remarks for enhancing the research studies were provided, and potential directions for future research were highlighted.

Kazeem B. Adedeji

Adnan M. Abu-Mahfouz

Anish M. Kurien

DDoS Attack and Detection Methods in Internet-Enabled Networks: Concept, Research Perspectives, and Challenges

互联网环境下DDoS攻击与检测方法：概念、研究视角与挑战

The control of active prostheses and orthoses requires the precise classification of instantaneous human activity and the detection of specific events within each activity. Furthermore, such classification helps physiotherapists, orthopedists, and neurologists in kinetic/kinematic analyses of patients’ gaits. To address this need, we propose an innovative deep neural network (DNN)-based approach with a two-step hyperparameter optimization scheme for classifying human activity and gait events, specific for different motor activities, by using the ENABL3S dataset. The proposed architecture sets the baseline accuracy to 93% with a single hidden layer and offers further improvement by adding more layers; however, the corresponding number of input neurons remains a crucial hyperparameter. Our two-step hyperparameter-tuning strategy is employed which first searches for an appropriate number of hidden layers and then carefully modulates the number of neurons within these layers using 10-fold cross-validation. This multi-class classifier significantly outperforms prior machine learning algorithms for both activity and gait event recognition. Notably, our proposed scheme achieves impressive accuracy rates of 98.1% and 99.96% for human activity and gait events per activity, respectively, potentially leading to significant advancements in prosthetic/orthotic controls, patient care, and rehabilitation programs’ definition.

Tasmiyah Javed

Ali Raza

Hafiz Farhan Maqbool

Saqib Zafar

Juri Taborri

Stefano Rossi

Multi-Class Classification of Human Activity and Gait Events Using Heterogeneous Sensors

使用异构传感器进行人体活动和步态事件的多类分类

The concurrence of social robots with different functionalities and cyber-physical systems in indoor environments has recently been increasing in many fields, such as medicine, education, and industry. In such scenarios, the collaboration of such heterogeneous robots demands effective communication for task completion. The concept of the Internet of Robotic Things (IoRT) is introduced as a potential solution, leveraging technologies like Artificial Intelligence, Cloud Computing, and Mesh Networks. This paper proposes an IoRT-based middleware that allows the communication of different types of robot operating systems in dynamic environments, using a cloud-based protocol. This middleware facilitates task assignment, training, and planning for heterogeneous robots, while enabling distributed communication via WiFi. The system operates in two control modes: local and cloud-based, for flexible communication and information distribution. This work highlights the challenges of current communication methods, particularly in ensuring information reach, agility, and handling diverse robots. To demonstrate the middleware suitability and applicability, an implementation of a proof-of-concept is shown in a touristic scenario where several guide robots can collaborate by effectively sharing information gathered from their heterogeneous sensor systems, with the aid of cloud processing or even internal communication processes. Results show that the performance of the middleware allows real-time applications for heterogeneous multi-robot systems in different domains.

Emil Cuadros Zegarra

Dennis Barrios Aranibar

Yudith Cardinale

IoRT-Based Middleware for Heterogeneous Multi-Robot Systems

基于IoRT的异构多机器人系统中间件

In this research, a novel interdigitated gear-shaped, graphene-based electrochemical biosensor was developed for the detection of dopamine (DA). The sensor’s innovative design improves the active surface area by 94.52% and 57% compared to commercially available Metrohm DropSens 110 screen-printed sensors and printed circular sensors, respectively. The screen-printed electrode was fabricated using laser processing and modified with graphene polyaniline conductive ink (G-PANI) to enhance its electrochemical properties. Fourier Transform Infrared (FTIR) Spectroscopy and X-ray diffraction (XRD) were employed to characterize the physiochemical properties of the sensor. Dopamine, a neurotransmitter crucial for several body functions, was detected within a linear range of 0.1–100 µM, with a Limit of Detection (LOD) of 0.043 µM (coefficient of determination, R2 = 0.98) in phosphate-buffer saline (PBS) with ferri/ferrocyanide as the redox probe. The performance of the sensor was evaluated using cyclic voltammetry (CV) and Chronoamperometry, demonstrating high sensitivity and selectivity. The interdigitated gear-shaped design exhibited excellent repeatability, with a relative standard deviation (RSD) of 1.2% (n = 4) and reproducibility, with an RSD of 2.3% (n = 4). In addition to detecting dopamine in human serum, the sensor effectively distinguished dopamine in a ternary mixture containing uric acid (UA) and ascorbic acid (AA). Overall, this novel sensor design offers a reliable, disposable, and cost-effective solution for dopamine detection, with potential applications in medical diagnostics and neurological research.

Pritu Parna Sarkar

Ridma Tabassum

Ahmed Jalal Hasnain

Ali Ashraf

Nazmul Islam

Interdigitated Gear-Shaped Screen-Printed Electrode Using G-PANI Ink for Sensitive Electrochemical Detection of Dopamine

交错齿轮形丝网印刷电极使用G-PANI墨水用于多巴胺的灵敏电化学检测

Smart farming is set to play a crucial role in the sustainable transformation of agriculture. The emergence of precision agriculture, facilitated by Internet of Things (IoT) platforms, makes effective communication among the various sensors and devices on farms essential. The development of smart sensors that utilize artificial intelligence (AI) algorithms for advanced edge computations only intensifies this need. Moreover, once data are collected, farmers frequently find it challenging to apply them effectively, especially in alignment with agroecological principles. In this context, this paper introduces an energy-efficient platform for embedded AI sensors that leverages the LoRaWAN network, along with a knowledge-based system to aid farmers in decision-making rooted in sensor data and agroecological practices. This paper focuses on the deployment of an end-to-end IoT platform that integrates a wireless sensor network (WSN), embedded AI, and a knowledge base.

Naila Bouchemal

Nicola Chollet

Amar Ramdane-Cherif

Intelligent IoT Platform for Agroecology: Testbed

农业生态智能物联网平台：试验台

With the rapid development of the metaverse, designing effective interfaces in virtual and augmented environments presents significant challenges. Additionally, keeping real-time sensory data flowing from users to their virtual avatars in a seamless and accurate manner is one of the biggest challenges in this domain. To this end, this article investigates a telepresence suit as an interface for interaction within the metaverse and its virtual avatars, aiming to address the complexities of signal generation, conversion, and transmission in real-time telepresence systems. We model a telepresence suit framework that systematically generates state data and transmits it to end-points, which can be either robotic avatars or virtual representations within a metaverse environment. Through a hand movement study, we successfully minimized the volume of transmitted information, reducing traffic by over 50%, which directly decreased channel load and packet delivery delay. For instance, as channel load decreases from 0.8 to 0.4, packet delivery delay is reduced by approximately half. This optimization not only enhances system responsiveness but also improves accuracy, particularly by reducing delays and errors in high-priority signal paths, enabling more precise and reliable telepresence interactions in metaverse settings.

Artem Volkov

Ammar Muthanna

Alexander Paramonov

Andrey Koucheryavy

Ibrahim A. Elgendy

Optimized Data Transmission and Signal Processing for Telepresence Suits in Multiverse Interactions

多重宇宙交互中远程呈现服装的优化数据传输与信号处理

Abbreviation	JSAN
Journal Impact	3.12
Quartiles(Global)	TELECOMMUNICATIONS(Q2)

Publication Information	Publisher: Multidisciplinary Digital Publishing Institute (MDPI)，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2012，Proportion of original research papers: 85.54%，Self Citation Rate:0.00%， Gold OA Rate: 100.00%
Journal Fees	$Details
Average review cycle	网友分享经验：11 Weeks

Journal of Sensor and Actuator Networks

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Security Vulnerabilities in Bluetooth Technology as Used in IoT

A Survey on Integrated Sensing, Communication, and Computing Networks for Smart Oceans

DDoS Attack and Detection Methods in Internet-Enabled Networks: Concept, Research Perspectives, and Challenges

Multi-Class Classification of Human Activity and Gait Events Using Heterogeneous Sensors

IoRT-Based Middleware for Heterogeneous Multi-Robot Systems

IoRT-Based Middleware for Heterogeneous Multi-Robot Systems

Multi-Class Classification of Human Activity and Gait Events Using Heterogeneous Sensors

Interdigitated Gear-Shaped Screen-Printed Electrode Using G-PANI Ink for Sensitive Electrochemical Detection of Dopamine

Intelligent IoT Platform for Agroecology: Testbed

Optimized Data Transmission and Signal Processing for Telepresence Suits in Multiverse Interactions

ISSN	2224-2708
h-index	39