Showing papers in "Internet of things in 2022"

The big picture on the internet of things and the smart city: a review of what we know and what we need to know

Abstract: This study examines how the application of the IoT in smart cities is discussed in the current academic literature. Based on bibliometric techniques, 1,802 articles were retrieved from the Scopus database and analyzed to identify the temporal nature of IoT research, the most relevant journals, authors, countries, keywords, and studies. The software tool VOSviewer was used to build the keyword co-occurrence network and to cluster the pertinent literature. Results show the significant growth of IoT research in recent years. The most productive authors, journals, and countries were also identified. The main findings from the keyword co-occurrence clustering and an in-depth qualitative analysis indicate that the IoT is used alongside other technologies including cloud computing, big data analytics, blockchain, artificial intelligence, and wireless telecommunication networks. The major applications of the IoT for smart cities include smart buildings, transportation, healthcare, smart parking, and smart grids. This review is one of the first attempts to map global IoT research in a smart city context and uses a comprehensive set of articles and bibliometric techniques to provide scholars and practitioners with an overview of what has been studied so far and to identify research gaps at the intersection of the IoT and the smart city.

A Review on Security and Privacy of Internet of Medical Things

Abstract: The Internet of Medical Things (IoMT) is increasing the accuracy, the reliability, and the production capability of electronic devices by playing a very important part in the industry of healthcare. The available medical resources and services related to the healthcare are working to get an interconnection with each other by the digital healthcare system by the contribution of the researchers. Sensors, wearable devices, medical devices, and clinical devices are all connected to form an ecosystem of the Internet of Medical Things. The different applications of healthcare are enabled by the Internet of Medical Things to reduce the healthcare costs, to attend the medical responses on time, and also to help in increasing the quality of the medical treatment. The healthcare industry is transformed by the Internet of Medical Things as it delivers targeted and personalized medical care, and it also seamlessly enables the communication of medical data. Devices used in the medical field and their application are connected to the system of healthcare with the help of the digital world.

In-home Health Monitoring using Floor-based Gait Tracking

Abstract: Gait assessments are commonly used for clinical evaluations of neurocognitive disease progression and general wellness. However, gait measurements in clinical settings do not accurately reflect gait in daily life. We present a non-wearable and unobtrusive method of detecting gait parameters in the home through the vibrations in the floor created by footfalls. Gait characteristics and gait asymmetry are estimated despite a low sensor density of 6.7 m 2 /sensor. Features from each footfall vibration signal is extracted and used to estimate gait parameters with gradient boosting regression and probabilistic models. Temporal gait asymmetry, locations of the footfalls, and peak tibial acceleration asymmetry can be predicted with a root mean square error of 0.013 s, 0.42 m, and 0.34 g respectively. This system allows for continuous at-home monitoring of gait which aids in early detection of gait anomalies.

Integrating IoT and AI for Indoor Air Quality Assessment

Abstract: This book presents Internet of Things (IoT) solutions monitoring and assessing a variety of applications areas for indoor air quality (IAQ).

AIOps: A Multivocal Literature Review

Abstract: In the age of Internet of Things (IoT) and big data, artificial intelligence for IT operations (AIOps) plays an important role in enhancing IT operations. Such operation tasks include automation, performance monitoring, and event correlations, among others. Although AIOps has proved to be important, it has not received much academic attention. Thus, by means of Multivocal Literature Review, this study is aiming to define AIOps, the benefits gained from it, the challenges an organization might face, and, finally, what lies in the foreseen future of the AIOps. The findings revealed that adopting AIOps helps in monitoring IT work, efficient time saving, improving human-AI collaboration, proactive IT work, and boosting faster mean time to recovery (MTTR). However, there are also reported challenges like doubt about the efficiency of artificial intelligence and machine learning, low-quality data, and identifying use cases, constrained by traditional engineering approaches. In conclusion, this study aims to contribute to the body of knowledge to the adaptation of AIOps in the IT industry which may benefit IT organizations. Finally, further research can be done to better understand how AIOps provides human augmentation to enhance human productivity in terms of senses, cognition, and human action.

Network Protocols for the Internet of Health Things

Abstract: With the expansion of technology, the Internet of Things (IoT) comprises keen gadgets, smart devices, wireless sensors, and systems that are a combination of updated innovations. Recently, low-power, low-latency gadgets are the most demanding devices in the healthcare sector. In this term, the network structure has changed a lot with the progress of wireless communications. Moreover, some research work explores that the next-generation network structure will be dependable on IoT, which signifies that the embedded devices can communicate with each other instantly. The arrangement of wireless and low-power, low-latency devices in medical science for IoT devices will have a life-changing impact on the healthcare system. This chapter will concentrate on various communication protocols and low-power, low-latency healthcare IoT devices. Furthermore, commonly IoT communication protocols, with an emphasis on the main features and behaviors of various metrics of power consumption, security spreading, data rate, and other features will also be distinguished, which will help in further research endeavors to select the correct convention for various applications.

IoT Ecosystem: Functioning Framework, Hierarchy of Knowledge, and Intelligence

Abstract: In the present era of advanced technology, IoT makes a vital contribution toward the development of sophisticated knowledge-aware systems for various growing sectors, like healthcare, education, intelligent cities, savvy homes, automized agriculture, etc. This chapter outlines an IoT framework, including the IoT ecosystem’s information and knowledge structure. Through an IoT ecosystem, core elements and their importance or meaning can be defined. In IoT-aware smart devices, smart sensors operate together over the Internet with limited or without human intervention. M2M (machine-to-machine) communication was the early stage of IoT in this Internet world. As IoT develops, it is using big innovations, including a vast array of statistical knowledge, machine learning, and artificial intelligence, to deal with large data and computations. This inquiry continues with an outline of the taxonomy of the IoT ecosystem. This chapter has formulated an overview of the IoT environment which illustrates IoT architecture, gateways, nodes, middleware, OS’s, framework, protection, storage and computation, communication or networking technologies of IoT, and interfaces for the efficient utilization of data in an ecosystem. This chapter moreover illustrates the hierarchy of the intelligence of the IoT ecosystem, which describes the process of generation of data, derivation of desired information from those raw data, processing, and manipulation. Collaborations between IoT and evolving technologies have been developed, including data processing (e.g., the use of machine learning algorithms), cloud, fog, and edge computing. Furthermore, several frameworks to ensure the security of data and the IoT ecosystem were elaborated based on machine learning. Finally, the chapter describes some applications of IoT that are growing faster.

Is the Internet of Things a helpful employee? An exploratory study of discourses of Canadian farmers

Abstract: The increasing global population and the growing demand for high-quality products have called for the modernization of agriculture. “Internet of Things” is one of the technologies that is predicted to offer many solutions. We conducted a discourse analysis of 19 interviews with farmers in Ontario, Canada, asking them to describe their experience of working with IoT and related technologies. One main discourse with two opposing tendencies was identified: farmers recognize their relationship with IoT and related technology and view technology as a kind of “employee”, but some tend to emphasize (1) an optimistic view which is discourse of technology is a “Helpful Employee”; while others tend to emphasize (2) a pessimistic view which is a discourse of technology is an “Untrustworthy Employee”. We examine these tendencies in the light of the literature on organizational behavior and identify potential outcomes of these beliefs. The results suggest that a farmer's style of approaching technology can be assessed on a similar scale as managers’ view of their employees and provide a framework for further research.

Attacking and Protecting Network Printers and VoIP Phones alike

Abstract: Printing over a network and calling over VoIP technology are routine at present. This article investigates to what extent these services can be attacked using freeware in the real world if they are not configured securely. In finding out that attacks of high impact, termed the Printjack and Phonejack families, could be mounted at least from insiders, the article also observes that secure configurations do not appear to be widely adopted. Users with the necessary skills may put existing security measures in place with printers, but would need novel measures, which the article prototypes, with phones in order for a pair of peers to call each other securely and without trusting anyone else, including sysadmins.

Classification of Swine Disease Using K-Nearest Neighbor Algorithm on Cloud-Based Framework

Abstract: A total of 25.9% of global jobs are occupied by the agriculture industry. As the global population grows, demand for both livestock and food production is growing rapidly. Many farmers live in rural parts of the nation and are in total doubt as to whether or not their livestock and crops are healthy. As a precautionary measure, they contact veterinary physicians to stop the transmission of illnesses to other healthy animals, which is counterproductive to their palatable fitness. By offering a cloud-based method to decide whether animals are safe or unsafe, this research aims to solve this issue. This research also aims to use supervised learning to conduct real-time classification, along with elucidating the device architecture that classifies photographs of diseased animals using the k-nearest neighbor (KNN) algorithm. A web cloud-based expert system was developed for the detection of swine diseases in pigs. MySQL was used for the cloud-based database which is at the backend of the website developed. PHP was used for the coding aspect of the system; the KNN algorithm was embedded into the PHP version 7.1.30. The developed system was able to predict disease that detects the likely occurrence of swine disease using ML algorithm. The system will allow farmers to input the symptoms noticed in the sick pigs, derive correct symptoms from a pig suffering a particular illness, and lastly prevent swine diseases from affecting other healthy pigs on the farm.

Smart Security for Industrial and Healthcare IoT Applications

Abstract: Adoption of Industrial Internet of Things (IIoT) can transform how industries operate and integrate IIoT to optimize the use of its assets and autonomously predict the failures and its maintenance processes by upholding the security with increased connectivity. IIoT thrive to provide smart security for cyber-physical systems and production processes in industries. The tremendous potential of IIoT has considerably reduced the workloads of professionals in the healthcare sector. IoT solutions provide assured time and energy to attend patients who are affected with chronic conditions and they can be monitored at home. IIoT vision in the world of healthcare is referred to as Internet of Healthcare Things (IoHT) or Internet of Medical Things (IoMT). Major use case of IIoT is to solve the interoperability challenges in collecting and analyzing patient data securely, to help in predicting and preventing adverse health conditions of patient, and to reduce the likelihood of patients’ readmission in hospitals. Managed security service providers (MSSPs) in industries and enterprises handle operational technologies which can be expected to be well-versed in the safety of workers and the quality of product. IIoT adopters empower the industries and enterprises with a secured setup and use their connected devices such as robotics, medical devices, and software-defined production processes with better efficiency and reliability in their operations.

Trust Models for Blockchain-Based Self-Sovereign Identity Management: A Survey and Research Directions

Abstract: Existing identity management systems either use a centralized authentication server or rely on identity providers to authenticate users for gaining access to various services. These systems have failed to safeguard user data privacy and do not encourage the portability of identity data. Self-sovereign identity is a new approach in identity management where entities have control of their digital identity. The emerging blockchain technology enables self-sovereign identity management, a decentralized identity management model that eliminates identity providers as a trusted third party. Due to the decentralized nature of blockchain network, this new paradigm of identity management demands different trust requirements. This research provides the first thorough review in literature addressing trust management for blockchain-based self-sovereign identity. A formal and comprehensive trust model proposed for blockchain-based Self-Sovereign IDM will be explored. Besides reviewing trust requirements, the paper also surveys the state-of-the-art of blockchain technology for self-sovereignty in identity management. This survey provides a critical analysis for existing research which sheds light on various opportunities for enhancing security and privacy of blockchain-based self-sovereign identity management and the improvement of trust management. The paper concludes with presenting research gaps and suggestions for future work in the area.

Resource Allocation in Time Slotted Channel Hopping (TSCH) Networks Based on Phasic Policy Gradient Reinforcement Learning

Abstract: The concept of the Industrial Internet of Things (IIoT) is gaining prominence due to its low-cost solutions and improved productivity of manufacturing processes. To address the ultra-high reliability and ultra-low power communication requirements of IIoT networks, Time Slotted Channel Hopping (TSCH) behavioral mode has been introduced in IEEE 802.15.4e standard. Scheduling the packet transmissions in IIoT networks is a difficult task owing to the limited resources and dynamic topology. In IEEE 802.15.4e TSCH, the design of the schedule is open to implementation. In this paper, we propose a phasic policy gradient (PPG) based TSCH schedule learning algorithm. We construct the utility function that accounts for the throughput, and energy efficiency of the TSCH network. The proposed PPG based scheduling algorithm overcomes the drawbacks of totally distributed and totally centralized deep reinforcement learning-based scheduling algorithms by employing the actor–critic policy gradient method that learns the scheduling algorithm in two phases, namely policy phase and auxiliary phase. In this method, we show that the schedule converges quickly compared to any other actor–critic method and also improves the system throughput performance by 58% compared to the minimal scheduling function, a default TSCH schedule. • We formulate resource scheduling in TSCH as a joint optimization problem. • Ours is the first work to design resource schedule based on the PPG learning method. • We model the utility function based on the QoS requirements of the network. • We compare the performance of PPG resource scheduling with other learning methods. • Our simulations show that PPG yields 58 % more throughput compared to standard (MSF).

A real-time tennis level evaluation and strokes classification system based on the Internet of Things

Abstract: In this study a single wearable inertial measurement unit (IMU) and machine learning methodologies were used to conduct player level evaluation and classification five prototype tennis strokes in real-time. The International Tennis Number (ITN) test was used to verify the accuracy of this IoT system in evaluating participant level. We conducted the ITN test on thirty-six participants and conducted one-way ANOVA on the ITN test results using IBM SPSS 26. The IMU in this study contained a tri-axis accelerometer (± 16 g) and tri-axis gyroscope (± 2000° /s) worn on the participants’ wrist connected to a wireless low-energy Bluetooth smart-phone with data sent to the computer terminal by cloud storage. Data processing including preprocessing, segmentation, feature extraction, dimensionality reduction and classification using Support Vector Machines (SVM), K-nearest neighbor (K-NN) and Naive Bayes (NB) algorithms. One-way ANOVA analysis predicting participants’ ITN level and ITN field test scores yielded p < 0.001 at the three different skill levels tested. SVM (MinMax), SVM (Standardiser) and SVM (MaxAbsScaler) classified unique tennis strokes precision and recall factors at the three different skill levels reliably yielded in f1-scores above 0.90 for serve, forehand and backhand, with f1-scores for forehand and backhand volley scores falling below that. The results of this study suggest using a single six-axial 50 Hz IMU in combination with SVM and SVM + PCA represents a significant step towards a more reliable wearable tennis stroke performance and skill level real-time evaluation and feedback technology.

Convergence Between IoT and AI for Smart Health and Predictive Medicine

Abstract: In the last years, the Internet of Things (IoT) has pilot the vision of a smarter world into reality with a massive amount of data and numerous services. The development of smart sensorial media and devices is getting remarkable attention from academia, government, industry, and healthcare communities. IoT-powered systems produce valuable sources of information and can transform healthcare. With the increase of healthcare services in non-clinical environments, which use vital signs provided by sensors and devices connected to patients, the need to mine and process the physiological measurements is growing significantly. The utilization of IoT to support healthcare is possible thanks to the artificial intelligence (AI). AI techniques, like natural language processing, data analytics, machine learning, and its sub-category deep learning, offer immense opportunities including disease diagnosis and monitoring, clinical workflow augmentation, and hospital optimization. The synergy between the IoT and AI is promising to monitor state of health of patients and to move upon traditional healthcare structures. Accompanied by communication technologies, cloud computing, and big data, it led to the emergence of the Smart Health concept. The chapter exhibits a literature review conducted to determine the most important technologies, methodologies, algorithms, and models for smart health systems. In addition, the main benefits and challenges of smart health were explored.

Intelligent Cyber-Physical Systems for Autonomous Transportation

Abstract: This book discusses the key topics related to the usage and deployment of AI in urban transportation systems including drones.

Preparing for Smart Cities’ Future Competences: Trends Arising Through Keyword and Review Analysis

Abstract: Nowadays, given the rapidity of recent technological advancements and their influence in all areas, key competences are needed as necessary requirements to cope with the complexity in different domains, where changes will become the norm in the future. Aiming to explore the topic of competences in smart cities, which is present at different disciplines, this study uses bibliometric analysis to achieve insight into new trends. The analysis was done on peer-reviewed journal articles and conference papers, published after 2010 in the Web of Science database. The publications are classified into distinct clusters so formed by using classifying techniques, hence, to make the voluminous data more understandable. This research firstly aims to contribute to the advancement of the understanding for the competence concept and relating researching aspects in the academic literature regarding smart cities by building a visual map of the keyword concepts used and obtain a conceptual atlas of the existing literature. Secondly, it studies recent competence reviews emphasizing the most relevant thesis in the area. The impact of this study will be an update to the pool of knowledge on smart cities’ competences needed to reflect needs not only for a specific group of persons but for all involved domain stakeholders.

Blockchain-Enabled Trust Management for Digital Marketing in the Industry 4.0 Era

Abstract: Blockchain technology is the fastest-developing technology in recent years, and it has had a significant impact on a wide range of industries and companies in the industry 4.0 era. Privacy, security, and trust are three of the most pressing issues facing digital marketing today. The purpose of this study is to investigate security, privacy, and trust challenges in digital marketing and how blockchain technology can be used to influence digital marketing to increase consumer trust and security. This was done via a systematic review of literature published between 2017 and 2021. The review identified that the use of blockchain technology in digital marketing and marketing management will continue to grow, and it has proven to be effective in providing solutions to both existing and upcoming company challenges and situations in industry 4.0. Blockchain can influence digital marketing by removing intermediaries and delivering trusted cybersecurity services with a high level of transparency and accountability. Also discussed are the possible problems and limitations of blockchain-enabled digital marketing.

An Interactive Analysis Platform for Bus Movement: A Case Study of One of the World’s Largest Annual Gathering

Abstract: Analysis of traffic conduct, mainly in densely populated urban areas, provides an excellent opportunity to study traffic patterns and extract useful information to help in planning and development. During activities that draw in a massive number of people, such as religious pilgrimages or sporting events, collisions of automotive traffic flows can result in interruptions and unsafe situations for the subjects, often creating chaos and congestion. The scenario becomes more ambitious in Hajj when millions of pilgrims move in a restricted area during a fixed period of time. Hajj is a 5-day Islamic pilgrimage whereby millions of pilgrims from across the globe assemble in Makkah to perform a number of spatiotemporal rituals every year on fixed dates. This chapter presents an interactive platform that utilizes large-scale GPS traces to detect the motion of buses during Hajj. For a period of 2 months, GPS traces are gathered for over 17,000 buses used to carry pilgrims performing Hajj activities. An interactive big data platform was developed to analyze and visualize the massive amount of spatial data. The analysis was done for various stakeholders, including the bus companies. Using our map-based visualization, they were able to visualize the movement of buses; identify drivers’ behavior, speed violations, and location of the violations; and determine the quality of data provided by various AVL providers. The information extracted can be used to generate an intelligent transportation system featuring schedule, evacuation, sustainability, resource optimization, and environmental and economic efficiencies to benefit stakeholders and improve the mobility of pilgrims throughout Hajj.

IoTracker: A probabilistic event tracking approach for data-intensive IoT Smart Applications

Abstract: Smart Applications for cities, industry, farming and healthcare use Internet of Things (IoT) approaches to improve the general quality. A dependency on smart applications implies that any misbehavior may impact our society with varying criticality levels, from simple inconveniences to life-threatening dangers. One critical challenge in this area is to overcome the side effects caused by data loss due to failures in software, hardware, and communication systems, which may also affect data logging systems. Event traceability and auditing may be impaired when an application makes automated decisions and the operating log is incomplete. In an environment where many events happen automatically, an audit system must understand, validate, and find the root causes of eventual failures. This paper presents a probabilistic approach to track sequences of events even in the face of logging data loss using Bayesian networks . The results of the performance analysis with three smart application scenarios show that this approach is valid to track events in the face of incomplete data. Also, scenarios modeled with Bayesian subnets highlight a decreasing complexity due to this divide and conquer strategy that reduces the number of elements involved. Consequently, the results improve and also reveal the potential for further advancement.

Processor power and energy consumption estimation techniques in IoT applications: A review

Abstract: The energy efficiency of IoT nodes remains the dominant factor for effective IoT solutions that will meet the challenges of the 21st century, especially in the drive towards a carbon-neutral world through net-zero targets. Microprocessors/microcontrollers are devices that perform entire operations of IoT devices. Therefore, the power and energy consumption of these processors directly reflects the power consumed by the IoT devices they drive. An accurate estimation of the power and energy consumption of the processors is vital for the development of energy-efficient IoT solutions because IoT devices are designed to operate in remote locations for long periods without human intervention. It is against this backdrop that this paper which is expected to serve as a guide for researches and IoT node/application developers in selecting the best technique for an IoT use-case, presents a review of processor power and energy consumption estimation techniques starting from the lowest level of abstraction to the highest level of abstraction. The review involves a detailed discussion of estimation technique methodologies for an abstraction level, and where applicable, generalized methodologies which cover the most approach used for an abstraction level are covered. The existence of overlaps and the impact of processor duty cycles on the techniques were discussed. A comparison of the strengths and weaknesses of each technique was made, from where register-transfer level and instruction level techniques are shown to be resilient against errors that occur from poor input signal conditioning. Future directions for the development of estimation techniques are also presented as recommendation.