IoT-enabled Devices Research Articles

Real-Time Environmental Monitoring for Aquaculture Using a LoRaWAN-Based IoT Sensor Network.

IoT-enabled devices are making it easier and cheaper than ever to capture in situ environmental data and deliver these data—in the form of graphical visualisations—to farmers in a matter of seconds. In this work we describe an aquaculture focused environmental monitoring network consisting of LoRaWAN-enabled atmospheric and marine sensors attached to buoys on Clyde River, located on the South Coast of New South Wales, Australia. This sensor network provides oyster farmers operating on the river with the capacity to make informed, accurate and rapid decisions that enhance their ability to respond to adverse environmental events—typically flooding and heat waves. The system represents an end-to-end approach that involves deploying a sensor network, analysing the data, creating visualisations in collaboration with farmers and delivering them to them in real-time via a website known as FarmDecisionTECH. We compared this network with previously available infrastructure, the results of which demonstrate that an in situ weather station was ∼5 C hotter than the closest available real-time weather station (∼20 km away from Clyde River) during a summertime heat wave. Heat waves can result in oysters dying due to exposure if temperatures rise above 30 C for extended periods of time (such as heat waves), which will mean a loss in income for the farmers; thus, this work stresses the need for accurate in situ monitoring to prevent the loss of oysters through informed farm management practices. Finally, an approach is proposed to present high-dimensional datasets captured from the sensor network to oyster farmers in a clear and informative manner.

Real-time monitoring and diagnosis scheme for IoT-enabled devices using multivariate SPC techniques

This article is aimed at condition monitoring and fault identification for Internet of Things (IoT) devices, and proposes a multivariate statistical process control scheme. The new method aims to detect sparse mean shifts using spatial rank and an improved adaptive elastic net algorithm, which can monitor the high-dimension data stream collected by IoT devices and pinpoint faulty variables. The new method is also applicable in the presence of a non-normal distribution and insufficient reference samples. Numerical simulations verify that the proposed method has clear advantages over existing methods. The case of wind turbines shows that the method can be applied to real-time monitoring and diagnosis of real IoT devices, which could provide valuable diagnosis of root cause and optimize subsequent maintenance strategies.

Cloud-Based Fault Prediction Using IoT in Office Automation for Improvisation of Health of Employees.

The novel paradigm of Internet of Things (IoT) is gaining recognition in the numerous scenarios promoting the pervasive presence of smart things around us through its application in various areas of society, which includes transportation, healthcare, industries, and agriculture. One more such application is in the smart office to monitor the health of devices via machine learning (ML) that makes the equipment more efficient by allowing real-time monitoring of their health. It guarantees indoor comfort as per the user's satisfaction as it emphasizes on fault prediction in real-life devices. Early identification of various types of faults in IoT devices is the key requirement in smart offices. IoT devices are becoming ubiquitous and provide an assistant to supervise an office that is regulated by ML and data received from sensors is stored in cloud. A recommender system facilitates the selection of an appropriate solution for faults in IoT-enabled devices to mitigate faults. The architecture proposed in this paper is used to monitor each and every office appliance connected via IoT technology using ML technique, and recommender system is used to recommend solutions for fault patterns without much human intervention. The ultrasonic motion sensor is used to fetch the information of employee availability in cubicles and data is sent to the cloud through the WiFi module. ATmega8 is used to control electrical appliances in the office environment. The significance of this work is to forecast the faults in IoT appliances which will have an impact on life and reliability of IoT appliances. The main objective is to design a prototype of a smart office using IoT that can control and automate workplace devices and forecast whether the device needs repairing or replacing, thus reducing the overall burden on the employee and helping out in increasing physical as well as mental health of the person.

Futuristic person re-identification over internet of biometrics things (IoBT): Technical potential versus practical reality

• Presents a futuristic multi-cue person re-identification over internet of biometrics things (IoBT) architecture. • Discusses the technical potential versus practical reality for achieving person reidentification over IoBT. • Highlights the importance of multi-cue PRId as a key component of smart-city surveillance. This article presents an overview of how person re-identification can be achieved over the Internet of Biometric Things (IoBT) architecture by enabling technologies and protocols for multimodal biometric authentication leveraging futuristic cues. The Internet of Things (IoT), as a new era of technology, extends the power of the internet to a whole range of devices, thus reshaping our daily lives in the best possible way. IoT-enabled intelligent surveillance devices are the most indispensable part of public safety and security in smart cities. These IoT devices generate a vast amount of surveillance traffic that is practically impossible for humans to continuously monitor and/or analyze. Person re-identification (PRId), which aims to track and recognize a person in a multi-camera scene is an important feature of visual surveillance systems in IoT infrastructures and can utilize the aforementioned traffic. This is where the concept of IoBT, which is a cloud-centric biometric authentication architecture composed of these IoT-enabled devices for the PRId system, comes into play. This article conceptualizes an overview of interpreting various futuristic cues on the IoT platform for achieving PRId. We highlight some opportunities and key challenges of implementing this futuristic PRId system on IoBT. The article is a proof of concept of the technical potential of such implementation in the near future.

A Conceptual Design of LoRa based Weather Monitoring System for Smart Farming

Internet of Things (IoT) based smart farming applications opens up new opportunities for monitoring the agricultural fields. There are different communication protocols can be used in practice to connect the IoT-enabled devices. Among them, the low-power, wide area network (LPWAN) based protocols are well suited to the specific needs of agricultural applications due to their energy-efficient transmission of small data packets over long distances. This study presents the conceptual design of LoRa based weather monitoring system that can be used to warn the farmers about possible crop damages due to harsh weather conditions. The hardware design of a low-cost weather station has been explained in details. Also, the estimated coverage area of the application to be carried out in order to reduce the risk of apple flowering frost damage risk in Karaman Province, Turkey was evaluated using the Xirio Online radio planning tool. The obtained results have verified the feasibility of proposed weather monitoring system.

LightIoT: Lightweight and secure communication for energy-efficient IoT in health informatics.

Internet of Things (IoT) is considered as a key enabler of health informatics. IoT-enabled devices are used for in-hospital and in-home patient monitoring to collect and transfer biomedical data pertaining to blood pressure, electrocardiography (ECG), blood sugar levels, body temperature, etc. Among these devices, wearables have found their presence in a wide range of healthcare applications. These devices generate data in real-time and transmit them to nearby gateways and remote servers for processing and visualization. The data transmitted by these devices are vulnerable to a range of adversarial threats, and as such, privacy and integrity need to be preserved. In this paper, we present LightIoT, a lightweight and secure communication approach for data exchanged among the devices of a healthcare infrastructure. LightIoT operates in three phases: initialization, pairing, and authentication. These phases ensure the reliable transmission of data by establishing secure sessions among the communicating entities (wearables, gateways and a remote server). Statistical results exhibit that our scheme is lightweight, robust, and resilient against a wide range of adversarial attacks and incurs much lower computational and communication overhead for the transmitted data in the presence of existing approaches.

An efficient authentication and key agreement protocol for IoT-enabled devices in distributed cloud computing architecture

With the widespread use of Internet of Things and cloud computing in smart cities, various security and privacy challenges may be encountered.The most basic problem is authentication between each application, such as participating users, IoT devices, distributed servers, authentication centers, etc. In 2020, Kang et al. improved an authentication protocol for IoT-Enabled devices in a distributed cloud computing environment and its main purpose was in order to prevent counterfeiting attacks in Amin et al.’ protocol, which was published in 2018. However, We found that the Kang et al.’s protocol still has a fatal vulnerability, that is, it is attacked by offline password guessing, and malicious users can easily obtain the master key of the control server. In this article, we extend their work to design a lightweight pseudonym identity based authentication and key agreement protocol using smart card. For illustrating the security of our protocol, we used the security protocol analysis tools of AVISPA and Scyther to prove that the protocol can defend against various existing attacks. We will further analyze the interaction between participants authentication path to ensure security protection from simulated attacks detailedly. In addition, based on the comparison of security functions and computing performance, our protocol is superior to the other two related protocols. As a result, the enhanced protocol will be efficient and secure in distributed cloud computing architecture for smart city.

On “Practical and secure outsourcing algorithms for solving quadratic congruences in IoTs” from IEEE IoT journal

Secure outsourced computation enables IoT devices to offload resource-intensive computations to a more resourceful server while keeping the inputs secret to the server. Recently, Zhang et al. put forth two outsourcing algorithms for solving quadratic congruences (Zhang et al., 2020). We observe that both the algorithms do not achieve the claimed security guarantees: a polynomial-time attack reveals the secret inputs to a passive adversary. As a consequence of the insecure outsourcing, the factorization of the RSA modulus is also revealed and hence leads to the total compromise of the security of the underlying scheme which makes use of the Zhang et al. outsourcing algorithms for solving quadratic congruences. Interestingly, we propose corrective measures for the Zhang et al. algorithm and prove that the resulting algorithm enables secure and verifiable delegation of solving quadratic congruences in IoTs.

SWIPT-Assisted Energy Efficiency Optimization in 5G/B5G Cooperative IoT Network

Resource use in point-to-point and point-to-multipoint communication emerges with the tremendous growth in wireless communication technologies. One of the technologies is wireless power transfer which may be used to provide sufficient resources for energy-constrained networks. With the implication of cooperative communication in 5G/B5G and the Internet of Things (IoT), simultaneous wireless information and power transfer (SWIPT)-assisted energy efficiency and appropriate resource use become challenging tasks. In this paper, multiple IoT-enabled devices are deployed to cooperate with the source node through intermediate/relay nodes powered by radio-frequency (RF) energy. The relay forwards the desired information generated by the source node to the IoT devices with the fusion of decode/amplify processes and charges itself at the same time through energy harvesting technology. In this regard, a problem with throughput, energy efficiency, and joint throughput with user admission maximization is formulated while assuring the useful, practical network constraints, which contemplate the upper/lower bounds of power transmitted by the source node, channel condition, and energy harvesting. The formulated problem is a mixed-integer non-linear problem (MINLP). To solve the formulated problem, the rate of individual IoT-enabled devices (b/s), number of selected IoT devices, and the sum-rate maximization are prosecuted for no-cooperation, cooperation with diversity, and cooperation without diversity. Moreover, a comparison of the outer approximation algorithm (OAA) and mesh adaptive direct search algorithm (MADS) for non-linear optimization with the exhaustive search algorithm is provided. The results with reference to the complexity of the algorithms have also been evaluated which show that 4.68×10−10 OAA and 7.81×10−11 MADS as a percent of ESA, respectively. Numerous simulations are carried out to exhibit the usefulness of the analysis to achieve the convergence to ε-optimal solution.

Tracking and Monitoring Fitness of Athletes Using IoT Enabled Wearables for Activity Recognition and Random Forest Algorithm for Performance Prediction

Purpose: The progression in technology is made the best use of in every field. Sports analytics is an essential sector that has gained importance in this technology-driven era. It is used to determine the hidden relationships among different quantitative parameters that affect the performance of athletes. This type of analysis requires a large amount of data to be stored periodically. Cloud acts as a scalable centralized repository that can store the massive data essential for analysis purpose. From the technological perspective there are numerous wearable activity tracking devices, which will be able to provide feedback of physical activities. With the help of random forest (RF) algorithm it is possible to classify huge datasets to perform predictions. In this paper, different smart devices that can be used to measure physical activity, use of RF algorithm for converting data obtained from smart devices into knowledge are explored. A conceptual model that uses wearable devices for tracking and monitoring and RF algorithm to predict the performance is suggested. Methodology: The study was conducted by referring to scholarly documents available online and by referring to websites of companies offering healthcare and sports related services. A conceptual model is developed based on the theoretical perception that incorporates the components needed for measuring the physical activities to predict the performance of athletes. Findings/Result: In this paper the proposed system contains four major activities as Capture, Store, Analyze, and Predict. The model considers use of IoT-enabled wearable devices to measure the physical activities of athletes and the information collected will in turn be used to analyze predict their performance and suggest them how to increase the chances of winning. However, the outcome of a game does not only depend upon the PA of athletes. It depends also upon the physical, mental, emotional health, nutrition and many other factors. Originality: In this paper, a theoretical model is deduced to integrate IoT and RF Algorithm to track and monitor fitness of athletes using wearables for activity recognition and performance prediction. Paper Type: Conceptual Paper

Modelling and analysis of artificial intelligence for commercial vehicle assembly process in VUCA world: a case study

Real-time monitoring, is now the integral component in smart manufacturing with the rapid application of Artificial Intelligence (AI) in manufacturing. Machine Learning (ML) algorithms and Internet of things (IoT) make the volatility, uncertainty, complexity, and ambiguity world (VUCA) more reliable and resilient with the stable industrial environment. In this study, two machine learning algorithms such as K-mean clustering and support vector, are used in combination with IoT-enabled embedded devices to design, deploy and test the effectiveness of the vehicle assembly process in the VUCA context. To accomplish this, the design includes both real-time data and training vector data, which were collected from IoT-enabled devices and evaluated using ML algorithms leading to the novel element called Smart Safe Factor (SSF), a critical threshold indicator that helps in limiting different units in assembly line-ups from excess wastages and energy losses in real-time. Test results highlight the impact of AI in enhancing the productivity and efficiency. Using SSF, 21.84% of energy is saved during the entire assembly process and 8% of excess stocks in storage have been curtailed for monetary benefits. This study deliberates the applications of AI and ML algorithms in a Vehicle Assembly (VA) model, connecting critical parameters such as cost, performance, energy, and productivity.

Intention to Use IoT by Aged Indian Consumers

ABSTRACT This study identifies the determinants which impact the intention to use the Internet of Things (IoT) enabled devices by the aged consumers of India for household purposes. With the help of the Model of Adoption of Technology in Households (MATH), a conceptual model has been developed. The model has been extended by considering two moderators (age and gender). It has been ascertained that the explanative power of the model after consideration of two moderators has been enhanced. Ten constructs of MATH have been considered which were found relevant to this study. The validation of the greater explainability by including two moderators in this modified MATH is considered as a theoretical contribution of this study. This study provides insight to the policy makers to understand how the aged consumers of India can be motivated to use IoT-enabled devices for their household purposes that would eventually improve their quality of life.

FRATO: Fog Resource Based Adaptive Task Offloading for Delay-Minimizing IoT Service Provisioning

In the IoT-based systems, the fog computing allows the fog nodes to offload and process tasks requested from IoT-enabled devices in a distributed manner instead of the centralized cloud servers to reduce the response delay. However, achieving such a benefit is still challenging in the systems with high rate of requests, which imply long queues of tasks in the fog nodes, thus exposing probably an inefficiency in terms of latency to offload the tasks. In addition, a complicated heterogeneous degree in the fog environment introduces an additional issue that many of single fogs can not process heavy tasks due to lack of available resources or limited computing capabilities. To cope with the situation, this article introduces FRATO (Fog Resource aware Adaptive Task Offloading) - a framework for the IoT-fog-cloud systems to offer the minimal service provisioning delay through an adaptive task offloading mechanism. Fundamentally, FRATO is based on the fog resource to select flexibly the optimal offloading policy, which in particular includes a collaborative task offloading solution based on the data fragment concept. In addition, two distributed fog resource allocation algorithms, namely TPRA and MaxRU are developed to deploy the optimized offloading solutions efficiently in cases of resource competition. Through the extensive simulation analysis, the FRATO-based service provisioning approaches show potential advantages in reducing the average delay significantly in the systems with high rate of service requests and heterogeneous fog environment compared with the existing solutions.

Delegated Key-Policy Attribute-Based Set Intersection over Outsourced Encrypted Data Sets for CloudIoT

Private set intersection (PSI) is a fundamental cryptographic primitive, allowing two parties to calculate the intersection of their data sets without exposing additional private information. In cloud-based IoT system, IoT-enabled devices would like to outsource their data sets in their encrypted form to the cloud. In this scenario, how to delegate the set intersection computation over outsourced encrypted data sets to the cloud and how to achieve the fine-grained access control for PSI without divulging any additional information to the cloud are still open problems. With that in mind, in this work, we combine key-policy attribute-based encryption (KP-ABE) and PSI to introduce such a novel concept, called delegated key-policy attribute-based set intersection over outsourced encrypted data sets (KP-ABSI), to solve this problem. Then we propose a first concrete KP-ABSI scheme and analyze its efficiency.

Applying the Teaching Factory Paradigm and Augmented Reality Technology for Operator Training in Assembly Operations

Educational and vocational training is constantly evolving due to the new technologies emergence under the concept of Industry 4.0. Augmented Reality (AR) is a rapidly growing technology that promises the delivery of high-quality visualization solutions, in a way that enables the user to interact with both digital and physical objects in a single immersive environment. This paper utilizes AR to support bilateral communication, between industry and academia, and enhance assembly and process monitoring operations, under the umbrella of the Teaching Factory paradigm. The proposed framework supports real-time information exchange between industrial equipment and the cloud-enabled AR application that empowers online performance monitoring and assembly operation support. The proposed approach utilizes IoT-enabled devices from the process ecosystem, in order to retrieve and upload information on a cloud-platform in real-time. Additional focus was given on ensuring the data distribution and visualization mechanisms, within different application instances in a non-geographical anchored network. Users from both industry and academia can simultaneously visualize and analyze process information within the AR environment, in the foreground of the physical or the digital equipment respectively. Further on, the application assisted the assembly operations of the process equipment, using animated holographic components for creating a realistic display of the of the assembly steps. The approach was implemented in a turbocharger system, using Android platform for the deployment of the AR application and an AllThingsTalk server for the data aggregation and distribution. The results indicated high potential on enhancing the process monitoring and assembly training, establishing a valuable tool for fast troubleshooting between users across industry and academia.

The safety of IoT-enabled system in smart cities of India: do ethics matter?

PurposeThe purpose of this study is to analyze the impact of ethics and technology towards safety of internet of things (IoT)-enabled system in smart cities of India (SCI).Design/methodology/approachThe determinants that would impact on securing IoT-enabled system in SCI have been identified by the studies of literature. Some hypothesis has been formulated. A conceptual model has been developed. Hypotheses and conceptual models have been tested by a statistical approach through survey works considering the feedbacks of 331 usable respondents. The results have been discussed followed by explaining the implications of this study. A comprehensive conclusion has been provided at the end.FindingsThe validated results show that the trust factor has insignificant impacts on the system and technology use, as well as on the behavioural intention. The model provided could achieve 79% explanative power.Practical implicationsFor ensuring safety and security of IoT-enabled devices in SCI, the ethical sense of the stakeholders of SCI has considerable impact on securing safety of IoT-enabled devices in SCI. The practitioner should, as such, be sincere to motivate the stakeholders to ameliorate the ethical sense of the stakeholders for securing safety of IoT-enabled devices in SCI.Originality/valueA few studies in the areas of Indian smart cities, IoT and related ethical issues have been conducted. In that sense, this approach is deemed to be a novel attempt.

Mid Square Hash Bezier Secured Routing for IoT Enabled Wireless Sensor Networks

The swift uptake of sensors and the increasing demand of Wireless Sensor Network (WSN) applications and services create unmatched appeals for routing data packets on WSN infrastructure. In the era of Internet of Things (IoT), an immense number of sensing devices collect numerous sensor data over time for an extensive span of fields. For IoT-enabled devices routing through WSN, sensor nodes transmit confidential data to the gateway nodes via public channels. In such an environment, secured routing remains a serious issue that has to be addressed. To address this issue, in this work, a robust method using Mid Square Hash-based Bezier Authentication (MSH-BA) is designed to secure the routing for IoT-enabled WSNs. First, a Mid Square Hashing Data Collection algorithm is proposed to minimize the energy consumption through unique key generation. To minimize the running time of IoT sensor network, discrete registration is performed between user and gateway nodes. Finally, the proof of correctness of mutual authentication is performed using the Bezier Authentication method via progressive distance, therefore ensuring packet delivery ratio. The robust authentication method is analyzed comprehensively and compared against the similar authentication methods and the results showed that it is efficient and robust than earlier methods.

Setting Up Telemedicine: Internet of Things to Support Rural Oncology Clinics in a Low- and Middle-Income Country—A Pilot Project in Kenya

PURPOSE The Internet of Things (IoT) is a technology that involves all things connected to the Internet that share data over a network without requiring human-to-human interaction or human-to-computer interaction. Information collected from IoT devices can help physicians identify the best treatment process for patients and reach accurate and expected outcomes. METHODS The International Cancer Institute is partnering to set up remote oncology clinics in sub-Saharan Africa. Medical oncologists and expert teams from across the world connect with oncology clinics in other Kenyan counties—Kisumu, Meru, Makueni, Garissa, Kakamega, Bungoma, Siaya, and Vihiga counties. The furthest county is Garissa, approximately 651.1 km from Eldoret, and the nearest is Vihiga at 100.4 km from Eldoret. This study began July 2019, and as of November 30th, the team has hosted 21 sessions with an average of 11 participants attending a session led by a medical oncologist. RESULTS IoT devices have become a way by which a patient gets all the information he or she needs from a physician without going to the clinic. Patient monitoring can be done in real time, allowing access to real-time information with improved patient treatment outcomes and a decrease in cost. Through IoT-enabled devices, the International Cancer Institute has set up weekly virtual tumor boards during which cancer cases are presented and discussed by all participating counties. An online training module on cancer is also offered. Furthermore, remote monitoring of a patient’s health helps to reduce the length of hospital stay and prevents readmissions. CONCLUSION In our setting, which has a few oncologists, use of IoT and tumor boards has helped to improve patient decision support as well as training for general physicians.

Analysis and Improvement on an Authentication Protocol for IoT-Enabled Devices in Distributed Cloud Computing Environment

Recently, a number of authentication protocols integrated with the Internet of Things (IoT) and cloud computing have been proposed for secure access control on large-scale IoT networks. In this paper, we carefully analyze Amin et al.’s authentication protocol for IoT-enabled devices in distributed cloud computing environment and find that Amin et al.’s protocol is vulnerable to several weaknesses. The main shortcoming of Amin et al.’s protocol is in authentication phase; a malicious cloud server can counterfeit the cloud server chosen by a user, and the control server cannot find this counterfeit. To overcome the shortcomings of Amin et al.’s protocol, we propose an improved protocol. In the registration phase of the improved protocol, the pseudoidentity and real identity of a user or a cloud server are bundled up with the control server’s secret numbers. This measure can effectively prevent impersonation attack. We also compare the improved protocol with several existing authentication protocols in security and computational efficiency.

Blockchain outlook for deployment of IoT in distribution networks and smart homes

Nowadays, unlike depleting fossil fuel resources, the integration of different types of renewable energy, as distributed generation sources, into power systems is accelerated and the technological development in this area is evolving at a frantic pace. Thus, inappropriate use of them will be irrecoverably detrimental. The power industry will reach a turning point in the pervasiveness of these infinite energy sources by three factors. Climate changes due to greenhouse gas accumulation in the atmosphere; increased demand for energy consumption all over the world, especially after the genesis of Bitcoin and base cryptocurrencies; and establishing a comprehensive perspective for the future of renewable energy. The increase in the pervasiveness of renewable energy sources in small-scale brings up new challenges for the power system operators to manage an abundant number of small-scale generation sources, called microsources. The current structure of banking systems is unable to handle such massive and high-frequency transactions. Thus the incorporation of cryptocurrencies is inevitable. In addition, by utilization of IoT-enabled devices, a large body of data will be produced must be securely transferred, stored, processed, and managed in order to boost the observability, controllability, and the level of autonomy of the smart power systems. Then the appropriate controlling measures must be performed through control signals in order to serve the loads in a stable, uninterruptible, reliable, and secure way. The data acquires from IoT devices must be analyzed using artificial intelligence methods such as big data techniques, data mining, machine learning, etc. with a scant delay or almost real-time. These measures are the controversial issues of modern power systems, which are yet a matter of debate. This study delves into the aforementioned challenges and opportunities, and the corresponding solutions for the incorporation of IoT and blockchain in power systems, particularly in the distribution level and residential section, are addressed. In the last section, the role of IoT in smart buildings and smart homes, especially for energy hubs schemes and the management of residential electric vehicle supply equipment is concisely discussed.