IoT-based Architectures Research Articles

PPFchain: A novel framework privacy-preserving blockchain-based federated learning method for sensor networks

Internet of Things (IoT) has been widely used in many smart applications such as smart cities, smart agriculture, healthcare, industry, etc. In addition, the importance of IoT-based architectures has increased with the emergence of innovative technologies such as 5G networks and quantum computing. Electrochemical sensors (ECS) have recently been used in IoT-based architectures thanks to their easy integration into smart systems in many fields such as pharmaceutical, food, medical diagnosis, clinical, genetic analysis, wearable, forensic identification, and monitoring of environmental variables. However, Although IoT-based systems have ensured the availability of sensor data in traditional architecture, there are many challenges, such as low latency, availability, real-time data traceability, and security. In addition, new challenges regarding security and privacy have emerged in the system as the ever-growing smart connected IoT devices generate a significant amount of heterogeneous data. Given these challenges, in this paper, we propose PPFchain, a new federated learning-enabled blockchain-based framework to ensure the security and privacy of sensor-IoT-based architectures using sampled ECS data. PPFchain has a lightweight, low-cost, high-performance architecture in the IoT-based blockchain network. In the architecture, we used the federated model and cryptographic primitives for user and data privacy in off-chain fog nodes considering performance. Moreover, we compared with traditional blockchain models using various performance metrics for system performance in a distributed architecture, such as an event and storage-based smart contract. In addition, the results show that the PPFchain provides accuracy, efficiency, and enhanced security.

Eaves: An IoT-Based Acoustic Social Distancing Assistant for Pandemic-Like Situations

In this article, we propose an IoT-based acoustic solution - Eaves - for ensuring social distancing in public areas during pandemic-like situations. Existing solutions depend on either sensing nearby radio signals such as Bluetooth or through image processing of video frames from surveillance cameras. Such methods either mandate the need for all parties to have the same application or impose line of sight constraints. We overcome such restrictions by using audio to ensure social distancing. The varying amplitude of the audio signals from different distances is the crux of the proposed method. Toward this, we record audio from different distances to extract human-voice-centric components and use the corresponding Mel-frequency cepstral coefficients. We train multiple machine learning models for selecting the one that predicts the distances efficiently with minimum delay and also propose possible IoT-based architectures to overcome resource limitations. Through extensive experiments and deployment, we observe a training accuracy of 97 percent and prediction accuracy of almost 100 percent up to 2 meters.

IoT-based airport systems: A unified approach towards establishing trust for high security and integrity of industrial IoT platforms and sensors

This paper introduces the latest research information on the emerging importance of internet of things (IoT) and edge or fog computing in modern Operational Technology (OT) based airport systems. It cites the novel aspects that arise as they become integral parts of critical systems such as airport; building automation; energy; environmental, physical and perimeter security; passenger processing and other airport systems. IoT-based sensors provide a whole new range of features considerably advanced than those of previous generations of sensors, by capturing and processing data and information at the source. Although the benefits of using IoT-based platforms and edge computing have proven a game changer for airport systems, aspects such as the privacy, security and safety and risk of utilising IoT-based architectures emerged from airport operators, as they were introduced and employed at airport operational environments. It is the aim of this paper to provide readers with the latest research on technologies that address those topics and their importance within an airport business and operational framework. This research has taken place in the context of CHARIOT project under the funding of Horizon programme by a consortium of companies that developed and validated those methods and tools that aim to address the privacy, security and safety aspects of IoT-based airport systems.

Driver Fatigue Detection Systems Using Multi-Sensors, Smartphone, and Cloud-Based Computing Platforms: A Comparative Analysis.

Internet of things (IoT) cloud-based applications deliver advanced solutions for smart cities to decrease traffic accidents caused by driver fatigue while driving on the road. Environmental conditions or driver behavior can ultimately lead to serious roadside accidents. In recent years, the authors have developed many low-cost, computerized, driver fatigue detection systems (DFDs) to help drivers, by using multi-sensors, and mobile and cloud-based computing architecture. To promote safe driving, these are the most current emerging platforms that were introduced in the past. In this paper, we reviewed state-of-the-art approaches for predicting unsafe driving styles using three common IoT-based architectures. The novelty of this article is to show major differences among multi-sensors, smartphone-based, and cloud-based architectures in multimodal feature processing. We discussed all of the problems that machine learning techniques faced in recent years, particularly the deep learning (DL) model, to predict driver hypovigilance, especially in terms of these three IoT-based architectures. Moreover, we performed state-of-the-art comparisons by using driving simulators to incorporate multimodal features of the driver. We also mention online data sources in this article to test and train network architecture in the field of DFDs on public available multimodal datasets. These comparisons assist other authors to continue future research in this domain. To evaluate the performance, we mention the major problems in these three architectures to help researchers use the best IoT-based architecture for detecting DFDs in a real-time environment. Moreover, the important factors of Multi-Access Edge Computing (MEC) and 5th generation (5G) networks are analyzed in the context of deep learning architecture to improve the response time of DFD systems. Lastly, it is concluded that there is a research gap when it comes to implementing the DFD systems on MEC and 5G technologies by using multimodal features and DL architecture.

A Secure IoT-Based Authentication System in Cloud Computing Environment.

The Internet of Things (IoT) is currently the most popular field in communication and information techniques. However, designing a secure and reliable authentication scheme for IoT-based architectures is still a challenge. In 2019, Zhou et al. showed that schemes pro-posed by Amin et al. and Maitra et al. are vulnerable to off-line guessing attacks, user tracking attacks, etc. On this basis, a lightweight authentication scheme based on IoT is proposed, and an authentication scheme based on IoT is proposed, which can resist various types of attacks and realize key security features such as user audit, mutual authentication, and session security. However, we found weaknesses in the scheme upon evaluation. Hence, we proposed an enhanced scheme based on their mechanism, thus achieving the security requirements and resisting well-known attacks.

Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk

Despite the perception people may have regarding the agricultural process, the reality is that today's agriculture industry is data-centered, precise, and smarter than ever. The rapid emergence of the Internet-of-Things (IoT) based technologies redesigned almost every industry including “smart agriculture” which moved the industry from statistical to quantitative approaches. Such revolutionary changes are shaking the existing agriculture methods and creating new opportunities along a range of challenges. This article highlights the potential of wireless sensors and IoT in agriculture, as well as the challenges expected to be faced when integrating this technology with the traditional farming practices. IoT devices and communication techniques associated with wireless sensors encountered in agriculture applications are analyzed in detail. What sensors are available for specific agriculture application, like soil preparation, crop status, irrigation, insect and pest detection are listed. How this technology helping the growers throughout the crop stages, from sowing until harvesting, packing and transportation is explained. Furthermore, the use of unmanned aerial vehicles for crop surveillance and other favorable applications such as optimizing crop yield is considered in this article. State-of-the-art IoT-based architectures and platforms used in agriculture are also highlighted wherever suitable. Finally, based on this thorough review, we identify current and future trends of IoT in agriculture and highlight potential research challenges.

Lightweight IoT-based authentication scheme in cloud computing circumstance

Recently, authentication technologies integrated with the Internet of Things (IoT) and cloud computing have been promptly investigated for secure data retrieval and robust access control on large-scale IoT networks. However, it does not have a best practice for simultaneously deploying IoT and cloud computing with robust security. In this study, we present a novel authentication scheme for IoT-based architectures combined with cloud servers. To pursue the best efficiency, lightweight crypto-modules, such as one-way hash function and exclusive-or operation, are adopted in our authentication scheme. It not only removes the computation burden but also makes our proposed scheme suitable for resource-limited objects, such as sensors or IoT devices. Through the formal verification delivered by Proverif, the security robustness of the proposed authentication scheme is guaranteed. Furthermore, the performance evaluation presents the practicability of our proposed scheme in which a user-acceptable computation cost is achieved.