Iot is a system of interconnected devices which are able to transfer data to and fro without the human-to-human interaction but over through other devices. IoT is now used for various purposes ranging from smart homes for controlling smart devices within the home, smart cities in which all the network devices operate synchronously, autonomous vehicles which is still a work in progress. With the advent of 5g comes the improvement in transmission rate, the number of devices available in square kilometer (...) and the elimination of congestion. The topic in discussion is reducing the food wastage in Australia by leveraging IoT. A large number of techniques are used to accomplish the said task such as qualitative analysis, inductive design and production data. The challenge is to maintain the freshness of the food by detecting the decay early on and warning the supplier when the food must be replaced thereby decreasing the wastage of food. The IoT devices requires to monitor the food, detect and alert the supplier when the food must be replaced. In this way the quality of the food can be supervised and reduce the wastage of the food. (shrink)

In an Internet of Things (IoT) environment, IoT devices are typically connected through different network media types such as mobile, wireless and wired networks. Due to the pervasive nature of such devices, they are a potential evidence source in both civil litigation and criminal investigations. It is, however, challenging to identify and acquire forensic artefacts from a broad range of devices, which have varying storage and communication capabilities. Hence, in this paper, we first propose an IoT network architecture for the (...) forensic purpose that uses machine learning algorithms to autonomously detect IoT devices. Then we posit the importance of focusing on the links between different IoT devices (e.g. whether one device is controlled or can be accessed from another device in the system), and design an approach to do so. Specifically, our approach adopts a graph for modelling IoT communications’ message flows to facilitate the identification of correlated network traffic based on the direction of the network and the associated attributes. To demonstrate how such an approach can be deployed in practice, we provide a proof of concept using two IoT controllers to generate 480 commands for controlling two IoT devices in a smart home environment and achieve an accuracy rate of 98.3% for detecting the links between devices. We also evaluate the proposed autonomous discovering of IoT devices and their activities in a TCP network by using real-world measurements from a public dataset of a popular off-the-shelf smart home deployed in two different locations. We selected 39 out of 81 different IoT devices for this evaluation. (shrink)

Precision agriculture is a breakthrough in digital farming technology, which facilitates the application of precise and exact amount of input level of water and fertilizer to the crop at the required time for increasing the yield. Since agriculture relies on direct rainfall than irrigation and the prediction of rainfall date is easily available from web source, the integration of rainfall prediction with precision agriculture helps to regulate the water consumption in farms. In this work, an edge computing model is developed (...) for predicting soil moisture in real time and managing the water usage in accordance with rain prediction. A soil moisture prediction hybrid algorithm has been developed that revolves around the decision-making techniques with live environmental parameters including weather parameters for the prediction of soil moisture through the impact of precipitation. Numerous algorithms with the combination of regression + clustering are estimated, and it is inferred that XGBoost + k-means outperforms other algorithmic combinations that is deployed in edge model. This model is used as an intermediary between the end IoT devices and cloud that results in the saving of computationally intensive processing performed on cloud servers. The servers located on a local edge network perform the developed algorithmic computations. Avoiding transmission over the cloud results in significant latency, response time, and computation power savings and therefore increases the efficiency of data transfer. The proposed edge computing model is implemented in Raspberry Pi as an edge, Heroku as cloud, and edge nodes as the combination of Pi with actuators and sensors. The monitored data from Pi are stored in MongoDB webserver that is controlled by Web dashboard. Finally, the developed model is implemented in cloud and edge where the edge server implementation performs better in terms of latency, bandwidth, throughput, response time, and CPU memory usage. (shrink)

The development and application scope of the Internet of Things is also becoming more and more extensive. Especially in the application of power testing improved systems, great progress has been made. This article aims to study how to analyze the system detection equipment based on the Internet of Things. This article describes the basic theoretical knowledge of the Internet of Things and power detection improved systems. A clustering analysis algorithm and a support vector machine algorithm based on the Internet of (...) Things are proposed. In the experiment of this article, the scoring items of the expert’s traditional detection system include complex technology, inconvenient use, and incomplete intelligence. Among them, the highest score for complex technology is 8.6 points, the lowest score is 7 points; the highest score for inconvenience is 8.6 points, and the lowest is 8.3 points. It can be seen that related experts believe that the traditional power detection improved system is not only very complicated in technology, very inconvenient to use but also incompletely intelligent. Therefore, it is very necessary to study the system detection equipment based on the Internet of Things. (shrink)

The IoT (Internet of Things) can transform businesses by automating processes ranging from inventory management to robotics to automation, saving time, and money. However, can small businesses benefit from the IoT? This article explores the emerging role of the IoT in small businesses, the impact on their ability to compete in a rapidly changing digital environment, and their awareness, attitudes, perceptions, and willingness to adopt it. The research utilizes an initial exploratory approach based on a review of case studies in (...) the literature, interviews with several economic development personnel and a few small and medium-size business managers. Benefits from the use of the IoT include increased efficiency in operations and reduced costs in businesses. The medium-size businesses interviewed have verified these benefits. However, the majority of economic development personnel and small businesses interviewed did not have much or any awareness of what IoT technologies were or their potential benefits. (shrink)

Public areas can have Internet of Things (IoT)-enabled sensing devices placed to keep track of possible security risks such as suspicious activity or misplaced possessions. In public areas, devices have the ability to gather information, but, in some cases, people must explicitly check out if they wish their data to be taken. This research presents an analysis of the IoT environment on Ganzhou’s public transportation, suggests a new IoT-based intelligent public transportation system framework, and shows how the communication network’s components (...) are being applied. In this study, we detail the deployment of IoT sensors through the collection of data. We proposed a novel Salp Swarm weighted recurrent neural network (SS- WRNN) for prediction in Ganzhou’s public transport flow. The data were extracted using linear discriminate analysis (LDA) from high-dimensional sensor data into a lower-dimensional space. For resolving the dynamic bus scheduling and controlling issues, decision support algorithms are suggested. It can help decision-makers decrease passenger trip times, boost scheduling effectiveness, and raise the rate at which transportation resources are utilized. (shrink)

Розвиток сучасного суспільства неможливий без використання в повсякденному житті цифрових засобів. Практична більшість населення України (16,6 млн. українців) має інтернет ресурс, це майже 39,3 %. На даний час головний показник користування «павутинням» – це наявність власного профілю у соцмережах. Станом на січень 2019р., відповідно до проведеного дослідження агенством PlusOne, мережею Facebook користувалось 13 млн. чол. Таким чином Україна займає 3 місце в світі за цим показником, поступаючись тільки Індії і Філіппінам. Вектор цифровізації, який обрала наша країна, починаючи з 2018р. кожну (...) добу стає більш доступним та відкритим для суспільства. Процес цифровізації полягає у досягненні цифрової трансформації існуючих та створенні нових галузей економіки, а також трансформації сфер життєдіяльності у нові більш ефективні та сучасні. Відповідно до концепції розвитку цифрової економіки та суспільства України на 2018–2020 рр., затвердженої Розпорядженням Кабінету Міністрів України від 17 січня 2018 р. № 67-р, цифровий розвиток передбачає виконання комплексу завдань, що позитивно вплинуть на економіку, бізнес, суспільство та життєдіяльність країни в цілому. Основними цілями цифрового розвитку є: - прискорення економічного зростання та залучення інвестицій; - трансформація секторів економіки в конкурентоспроможні та ефективні; - технологічна та цифрова модернізація промисловості та створення високотехнологічних виробництв; - доступність для громадян переваг та можливостей цифрового світу; - реалізація людського ресурсу, розвиток цифрових індустрій та цифрового підприємництва. Основними рейтинговими цілями реалізації Концепції є досягнення у 2020 році: - 30 місце в рейтингу Networked Readiness Index (WEF) (у 2016 році - 64 місце); - 40 місце у рейтингу Global Innovation Index (INSEAD, WIPO) (у 2016 році - 56 місце); - 50 місце у рейтингу ICT Development Index (ITU) (у 2016 році - 79 місце); - 60 місце у рейтингу Global Competitiveness Index (WEF) (у 2016 році - 85 місце) [1]. Економіка та індустрія країни повинна бути конкурентоспроможною, подолати цифровий розрив, розбудовувати цифрову інфраструктуру та стати на шлях промислової революції 4.0. Індустрія 4.0 - оновлена концепція “розумного виробництва”, що ототожнюється з “четвертою промисловою революцією” та появою кіберфізичних систем. Індустрія 4.0 - наступний етап цифровізації виробництв та промисловості, на якому головну роль відіграють такі технології та концепти, як Інтернет речей, “великі дані” (big data), “предиктивна аналітика”, хмарні та туманні обчислення, “машинне навчання”, машинна взаємодія, штучний інтелект, робототехніка, 3D-друк, доповнена реальність. Інтеграція цифрових технологій у процеси виробництва, або цифровізація промисловості, є пріоритетом державної промислової політики. Державна політика стимулювання розвитку Індустрії 4.0 має три напрями: - створення інфраструктури Індустрії 4.0 - індустріальних парків, галузевих центрів технологій тощо; - доступ до капіталу для створення нових інноваційних виробництв; - розвиток цифрових навичок для підготовки персоналу, здатного працювати з технологіями Індустрії 4.0. [1]. Одним із вирішальних та найголовніших блоків Індустрії 4.0 є інтернет речей (IoT). У 1999 році британський технолог Кевін Ештон придумав термін «Інтернет речей» (IoT), щоб визначити мережу, яка об'єднує не тільки людей, а й навколишні їх об'єкти. У той час більшість людей думали, що це матеріал науково-фантастичних фільмів. Сьогодні, Інтернет речей - велика мережа інтелектуальних об'єктів, які працюють разом для збору і аналізу даних і автономного виконання дій - стає реальністю завдяки технології між машинного зв'язку (M2M). Багато в чому розумні об'єкти використовувалися протягом десятиліть, такі як електронний наручний годинник, автосигналізація і скоординовані світлофори. Те, що дає IoT, - це велика поширеність інтелектуальних об'єктів і більш висока зв'язок між ними. Очікується, що до кінця 2019 року глобальний ринок Інтернету речей (IoT) виросте до 212 млрд. дол.. Вперше в 2017 році технологія досягла 100 млрд. дол. доходу від ринку, і, згідно з прогнозами, ця цифра буде зростати приблизно до 1,6 трлн (прогнозний 2025 р.) (Рис.1.) [2]. Проаналізуємо за продуктовою та географічною сегментацією ринок IoT. За продуктовою сегментацією ринок IoT включає: - IoT промисловості. Очікується, що виробництво стане найбільшим сегментом платформи IoT, який до 2021 року досягне $ 438 млн.дол. Компанії усвідомлюють переваги підключення промислового обладнання для оптимізації операцій і зниження витрат. - Smart місто. У розумних містах спостерігається найбільше зростання за 6-річний період (54% CAGR). - Smart home. Розумний будинок і пристрої є першими лідерами ринку IoT, проте очікується, що більш повільні темпи впровадження зменшать зростання до 18% і 11% відповідно протягом 6-річного періоду на відміну від інших швидкозростаючих сегментів Інтернету речей. Рис.1. Динаміка IoT 2017-2025 рр. Провідними географічними сегментами на ринку IoT є Північна Америка, Азія та Європа. У регіоні Північної Америки до 2021 року буде спостерігатися найвищий показник CAGR - 36%, враховуючи, що США є одним з піонерів платформ IoT: більшість провідних постачальників платформ IoT базуються в США. Проте, Азія з 35% - ним зростанням стане найбільшим континентальним ринком (2021 рік: 616 млн. дол). До 2021 року Китай стане провідною азійською країною на ринку IoT. Сполучені Штати в даний час є лідером на ринку платформ IoT в Північній Америці, а також найбільшою країною світу з обсягом ринку 73 млн. дол. у 2015 році, і очікується, що США залишиться на першому місці в 2021 році з обсягом 469 млн дол. За лідером будуть прямувати Китай (180 млн дол.), Німеччина (136 млн дол.), Японія (127 млн дол.), Корея (118 млн дол.) [3]. (shrink)

Recently, a number of ontology-driven healthcare systems have been leveraged by the Internet-of-Things (IoT) technologies that offer opportunities to improve abnormal situation detection when integ...

Internet-of-Things (IoT) creates a significant impact in spectrum sensing, information retrieval, medical analysis, traffic management, etc. These applications require continuous information to perform a specific task. At the time, various intermediate attacks such as jamming, priority violation attacks, and spectrum poisoning attacks affect communication because of the open nature of wireless communication. These attacks create security and privacy issues while making data communication. Therefore, a new method autoencoder deep neural network (AENN) is developed by considering exploratory, evasion, causative, and priority (...) violation attack. The created method classifies the transmission outcomes used to predict the transmission state, whether it is jam data transmission or sensing data. After that, the sensing data is applied for network training that predicts the intermediate attacks. In addition to this, the channel access algorithm is used to validate the channel for every access that minimizes unauthorized access. After validating the channel according to the neural network, data have been transmitted over the network. The defined process is implemented, and the system minimizes different attacks on various levels of energy consumption. The effectiveness of the system is implemented using TensorFlow, and the system ensures the 99.02% of detection rate when compared with other techniques. (shrink)

We design and implement an intelligent IoT-based motion monitoring system to realize the monitoring of three important parameters, namely, the type of movement, the number of movements, and the period of movement in physical activities, and optimize the system to support the simultaneous use by multiple users. Considering the motion monitoring scenario for smart fit, the framework of an IoT-based motion monitoring system is proposed. The framework contains components such as active acquisition nodes, wireless access points, data processing servers, and (...) terminals. In terms of algorithm optimization, research related to active pattern recognition and periodic calculation methods is conducted. For active pattern recognition, two types of classification algorithms with different complexity are proposed based on Support Vector Machine and deep neural networks, respectively, to adapt to scenarios with different computational capabilities. For period calculation, a method based on over-zero detection and wavelet transform is proposed to count the number of actions and calculate the period of each action. In 100 times action cycle calculation experiments, the count statistic calculation method achieves 100% calculation accuracy and the active cycle calculation results are close to the real value, which proves the effectiveness of the cycle calculation method. The system provides a multiuser-oriented communication method and realizes accurate and reliable human movement monitoring, which has a wide application prospect in the fields of physical education and rehabilitation training. (shrink)

Most of the IoT-based smart systems require low latency and crisp response time for their applications. Achieving the demand of this high Quality of Service becomes quite challenging when computationally intensive tasks are offloaded to the cloud for execution. Edge computing therein plays an important role by introducing low network latency, quick response, and high bandwidth. However, offloading computations at a large scale overwhelms the edge server with many requests and the scalability issue originates. To address the above issues, an (...) efficient resource management technique is required to maintain the workload over the edge and ensure the reduction of response time for IoT applications. Therefore, in this paper, we introduce a metaheuristic and nature-inspired Artificial Bee Colony optimization technique that effectively manages the workload over the edge server under the strict constraints of low network latency and quick response time. The numerical results show that the proposed ABC algorithm has outperformed Particle Swarm Optimization, Ant Colony Optimization, and Round-Robin Scheduling algorithms by producing low response time and effectively managing the workload over the edge server. Furthermore, the proposed technique scales the edge server to meet the demand of high QoS for IoT applications. (shrink)

In this paper, we propose an Internet of Things to enhancing the experience of personal gardening as a method of therapy for mental-health patients, given a belief in its role in a person’s mood and general positivity, The proposed prototype continuously senses and monitors the state of an indoor plant through different sensors. The user is notified of the plant’s needs for water, sunlight, etc., through generated notifications from channels over cloud in-real time. Thus, we were able to successfully create (...) a humanised experience of recovery where the user can accessibly ‘talk’ with its plant through a smartphone. (shrink)

Since the 1970s, the application of microprocessor in industrial machinery and the development of computer systems have transformed the manufacturing landscape. The rapid integration and automation of production systems have outpaced the development of suitable human design criteria, creating a deepening gap between humans and systems in which human was seen as an important source of errors and disruptions. Today, the situation seems different: the scientific and public debate about the concept of Industry 4.0 has raised awareness about the central (...) role humans have to play in manufacturing systems, the design of which must be considered from the very beginning. The future of industrial systems, as represented by Industry 4.0, will rely on the convergence of several research fields such as Intelligent Manufacturing Systems (IMS), Cyber-Physical Systems (CPS), Internet of Things (IoT), but also socio-technical fields such as social approaches within technical systems. This article deals with different human social dimensions associated with CPS and IoT and focuses on their conceptual evolution regarding automated production systems’ sociability, notably by bringing humans back in the loop. Hereby, this paper aims to take stock of current research trends to show the importance of integrating human operators as a part of a socio-technical system based autonomous and intelligent products or resources. Consequently, different models of sociability as a way to integrate humans in the broad sense and/or the develop future automated production systems have been identified from the literature and analysed. (shrink)

An intelligent climate and watering agriculture system is presented that is controlled with Android application for smart water consumption considering small and medium ruler agricultural fields. Data privacy and security as a big challenge in current Internet of Things (IoT) applications, as with the increase in number of connecting devices, these devices are now more vulnerable to security threats. An intelligent fuzzy logic and blockchain technology is implemented for timely analysis and securing the network. The proposed design consists of various (...) sensors that collect real-time data from environment and field such as temperature, soil moisture, light intensity, and humidity. The sensed field information is stored in IoT cloud platform, and after the analysis of entries, watering is scheduled by implementing the intelligent fuzzy logic and blockchain. The intelligent fuzzy logic based on different set of rules for making smart decisions to meet the watering requirements of plant and blockchain technology provides necessary security to the IoT-enabled system. The implementation of blockchain technology allows access only to the trusted devices and manages the network. From the experimentation, it is observed that the proposed system is highly scalable and secure. Multiple users at the same time can monitor and interact with the system remotely by using the proposed intelligent agricultural system. The decisions are taken by applying intelligent fuzzy logic based on input variables, and an alert is transmitted about watering requirements of a field to the user. The proposed system is capable of notifying users for turning water motor on and off. The experimental outcomes of the proposed system also reveal that it is an efficient and highly secure application, which is capable of handling the process of watering the plants. (shrink)

The Internet of Things (IoT) is a fast-growing technology that connects everyday devices to the Internet, enabling wireless, low-consumption and low-cost communication and data exchange. IoT has revolutionized the way devices interact with each other and the internet. The more devices become connected, the greater the risk of security breaches. There is currently a need for new approaches to algorithms that can detect malware regardless of the size of the network and that can adapt to dynamic changes in the network. (...) Through the use of a multi-agent reinforcement learning algorithm, this paper proposes a novel algorithm for malware detection in IoT devices. The proposed algorithm is not strongly dependent on the size of the IoT network due to the that its training is adapted using time differences if the IoT network size is small or Monte Carlo otherwise. To validate the proposed algorithm in an environment as close to reality as possible, we proposed a scenario based on a real IoT network, where we tested different malware propagation models. Different simulations varying the number of agents and nodes in the IoT network have been developed. The result of these simulations proves the efficiency and adaptability of the proposed algorithm in detecting malware, regardless of the malware propagation model. (shrink)

This paper looks at the development of blockchain technologies that promise to bring new tools for the management of private data, providing enhanced security and privacy to individuals. Particular interest present solutions aimed at reorganizing data flows in the Internet of Things architectures, enabling the secure and decentralized exchange of data between network participants. However, as this paper argues, the promised benefits are counterbalanced by a significant shift towards the propertization of private data, underlying these proposals. Considering the unique capacity (...) of blockchain technology applications to imitate and even replace traditional institutions, this aspect may present certain challenges, both of technical and ethical character. In order to highlight these challenges and associated concerns, this paper identifies the underlying techno-economic factors and normative assumptions defining the development of these solutions amounting to technologically enabled propertization. It is argued that without careful consideration of a wider impact, such blockchain applications could have effects opposite to the intended ones, thus contributing to the erosion of privacy for IoT users. (shrink)

The advance in Internet of Things technology has increased the opportunities for a healthcare system design, which is an urgent need owing to the growth in population among the older adults in many countries. This requires giving thought to the kind of innovative technological design methods that can find suitable solutions for home care. The application of Health Smart Homes by means of the technologies of the Internet of Things, can be used to support rehabilitation treatment and help the senior (...) citizens to understand the importance of taking measures to maintain a healthy standard of living that can meet their needs. The aim of this article is to develop and assess a design method for the following purposes: to determine and map out the physical and emotional state of the home care users, such as senior citizens; to implement a participatory design that includes the user within its social, psychological and therapeutic context; to explore the flexible method when applied to older users; to provide a way for the users to be “personalized” through a wide range of solutions that involve analyzing the behavioral patterns of different individuals in a standardized manner and to define a set of smart technologies for each problem and senior citizen. This article sets out a collaborative method called FlexPersonas, which is employed for the flexible mapping of users and to improve decision-making with the support of Internet of Things technologies. In this context, computing systems can identify the behavior of the user and issue warnings to the Carers about any abnormal event. Studies with an interdisciplinary team point out the potential and drawbacks of the method. (shrink)

The rapid urbanization of modern cities necessitates innovative approaches to data collection and integration for smarter urban management. With the Internet of Things (IoT) at the core of these advancements, the ability to efficiently gather, analyze, and utilize data becomes paramount. Generative Artificial Intelligence (AI) is revolutionizing data collection by enabling intelligent synthesis, anomaly detection, and real-time decision-making across interconnected systems. This paper explores how generative AI enhances IoT-driven data collection in smart cities, focusing on applications in transportation, energy, public (...) safety, and environmental monitoring. By addressing challenges such as data privacy, scalability, and ethical considerations, the study highlights how generative AI transforms urban governance and paves the way for sustainable and citizen-centric development. Key trends, case studies, and future research directions are discussed, showcasing the potential of generative AI as a cornerstone of smart city initiatives. (shrink)

The large number of sensors and actuators that make up the Internet of Things obliges these systems to use diverse technologies and protocols. This means that IoT networks are more heterogeneous than traditional networks. This gives rise to new challenges in cybersecurity to protect these systems and devices which are characterized by being connected continuously to the Internet. Intrusion detection systems are used to protect IoT systems from the various anomalies and attacks at the network level. Intrusion Detection Systems can (...) be improved through machine learning techniques. Our work focuses on creating classification models that can feed an IDS using a dataset containing frames under attacks of an IoT system that uses the MQTT protocol. We have addressed two types of method for classifying the attacks, ensemble methods and deep learning models, more specifically recurrent networks with very satisfactory results. (shrink)

The influential stage of Internet of Things has reformed all fields of life in general but specifically with the emergence of artificial intelligence has drawn the attention of researchers into a new paradigm of life standard. This revolution has been accepted around the globe for making life easier with the use of intelligent devices such as smart sensors, actuators, and many other devices. AI-enabled devices are more intelligent and capable of doing a specific task which saves a lot of resources (...) and time. Different approaches are available in the existing literature to tackle diverse issues of real life based on AI and IoT systems. The role of decision-making has its own importance in the AI-enabled and IoT systems. In-depth knowledge of the existing literature is dire need of the research community to summarize the literature in effective way by which practitioners and researchers can benefit from the prevailing proofs and suggest new solutions for solving a particular problem of AI-enabled sensing and decision-making for the IoT system. To facilitate research community, the proposed study presents a systematic literature review of the existing literature, organizes the evidences in a systematic way, and then analyzes it for future research. The study reported the literature of the last 5 years based on the research questions, inclusion and exclusion criteria, and quality assessment of the selected study. Finally, derivations are drawn from the included paper for future research. (shrink)

Smart parsimonious and economical ways of irrigation have build up to fulfill the sweet water requirements for the habitants of this world. In other words, water consumption should be frugal enough to save restricted sweet water resources. The major portion of water was wasted due to incompetent ways of irrigation. We utilized a smart approach professionally capable of using ontology to make 50% of the decision, and the other 50% of the decision relies on the sensor data values. The decision (...) from the ontology and the sensor values collectively become the source of the final decision which is the result of a machine learning algorithm. Moreover, an edge server is introduced between the main IoT server and the GSM module. This method will not only avoid the overburden of the IoT server for data processing but also reduce the latency rate. This approach connects Internet of Things with a network of sensors to resourcefully trace all the data, analyze the data at the edge server, transfer only some particular data to the main IoT server to predict the watering requirements for a field of crops, and display the result by using an android application edge. (shrink)

The influential stage of Internet of Things has reformed all fields of life in general but specifically with the emergence of artificial intelligence has drawn the attention of researchers into a new paradigm of life standard. This revolution has been accepted around the globe for making life easier with the use of intelligent devices such as smart sensors, actuators, and many other devices. AI-enabled devices are more intelligent and capable of doing a specific task which saves a lot of resources (...) and time. Different approaches are available in the existing literature to tackle diverse issues of real life based on AI and IoT systems. The role of decision-making has its own importance in the AI-enabled and IoT systems. In-depth knowledge of the existing literature is dire need of the research community to summarize the literature in effective way by which practitioners and researchers can benefit from the prevailing proofs and suggest new solutions for solving a particular problem of AI-enabled sensing and decision-making for the IoT system. To facilitate research community, the proposed study presents a systematic literature review of the existing literature, organizes the evidences in a systematic way, and then analyzes it for future research. The study reported the literature of the last 5 years based on the research questions, inclusion and exclusion criteria, and quality assessment of the selected study. Finally, derivations are drawn from the included paper for future research. (shrink)

The Internet of Things (IoT) presents a unique cybersecurity challenge due to its vast network of interconnected, resource-constrained devices. These vulnerabilities not only threaten data integrity but also the overall functionality of IoT systems. This study addresses these challenges by exploring efficient data reduction techniques within a model-based intrusion detection system (IDS) for IoT environments. Specifically, the study explores the efficacy of an autoencoder’s latent space combined with three different classification techniques. Utilizing a validated IoT dataset, particularly focusing on the (...) Constrained Application Protocol (CoAP), the study seeks to develop a robust model capable of identifying security breaches targeting this protocol. The research culminates in a comprehensive evaluation, presenting encouraging results that demonstrate the effectiveness of the proposed methodologies in strengthening IoT cybersecurity with more than a 99% of precision using only 2 learned features. (shrink)

El reto de los sistemas educativos ha sido proponer escenarios virtuales con mediación eficiente de tecnología que faciliten la evidencia de desarrollo tecnológico. Nuestra propuesta tiene como objetivo definir una estrategia de aprendizaje que permita el desarrollo tecnológico a través del uso de simuladores basados en IoT y la interacción de servidores en la nube para el almacenamiento de datos. Se pretende convertir al instructor en un guía tecnológico que permita verificar los resultados del aprendizaje. La propuesta facilita el desarrollo (...) de competencias computacionales enfocadas a la creación tecnológica con escenarios dinámicos y configurables para ser accesibles desde la web. (shrink)

Smart communities have recently gained much attention. Researchers have been trying to tackle a number of challenges faced by smart communities. Interoperability is one key challenge that occurs due to different systems using different knowledge representations. To solve interoperability problems, ontologies are seen as a promising solution as they provide a commonly agreed vocabulary for representing data that are understandable by stakeholders of smart communities. Smart communities make use of Internet of Things (IoT) and ubiquitous networks to support communication among (...) objects and devices in such environments. Smart campuses are examples of smart communities. Recently, many articles related to ontologies focusing on smart communities and smart campuses in IoT environments, have been published. This paper presents a Systematic Literature Review that has been conducted using Google Scholar. 18 ontologies for smart communities/smart campuses have been identified and analyzed out of 341 articles from year 2010 to 2019. The review classifies the ontologies in terms of domain, ontologies being reused, availability online, limitations, language adopted and coverage. It additionally discusses on the standards, the level of expressiveness, the ontology development approaches and methodologies adopted by the identified ontologies. Our analysis shows that the identified ontologies have been developed based on different ontological commitments. None of them have come up with a core semantic model that models different collaborating domains in a smart campus such as smart learning, smart management, smart governance, smart room, smart health, smart library and smart parking among others and that enhances cross-domain interoperability in a such an environment. Further details on our findings are presented and discussed in the paper. (shrink)

Internet of thing building sensors can capture several types of building operations, performances, and conditions and send them to a central dashboard to analyze data to support decision-making. Traditionally, laptops and cell phones are the majority of Internet-connected devices. IoT tracking allows customers to close the distance between devices and enterprises by collecting and analyzing various IoT data through connected devices, customers, and applications on the network. There is a lack of requirements for IoT edge applications security and approval. There (...) are no best practices regarding operations focused on IoT incidents. IoT elements are not covered by audit and logging requirements. In this article, a big data analytics-based customer operation system analyzes the operation. With the exponential rise in data usage, the explosive development in the IoT devices reflects the ideal overlap of big data growth with IoT. Big data analytics continuously evolving network raises trivial questions about the performance, distribution of data, analysis, and protection of data collection. IoT modifies almost all the construction industry characteristics. Human-centered artificial intelligence is described as systems that always improve because of human input while also delivering an effective experience between the human and the robotic. The IoT is the key factor that ensures greater building performance. It was the first evolution of technology in a long time to turn genuine inventions into an industry that depended heavily on paper and manual processes. The benefits of the IoT in construction are now quite obviously much heavier than those of current manual processes. As a result, more construction companies explore and incorporate IoT strategies to address their productivity challenges, increasing efficiencies and profits. The simulation analysis shows that the proposed BDA-CO model enhances the trust score of 98.5%, accuracy detection ratio of 93.4%, probability ratio of 97.6%, and security ratio of 98.7% and reduces the false negative ratio of 21.3%, response time of 10.5%, delay rate of 19.9%, and packet loss ratio of 15.4% when compared to other existing techniques. (shrink)

Motivated by advances in mass customization in business practice, explosion in the number of internet of things devices, and the lack of published research on privacy differentiation and customization, we propose a contextual information relevance model of privacy. We acknowledge the existence of individual differences with respect to unique security and privacy protection needs. We observe and argue that it is unfair and socially inefficient to treat privacy in a uniform manner whereby a large proportion of the population remain unsatisfied (...) by a common policy. Our research results provide quantifiable means to measure and evaluate the customized privacy. We show that with privacy differentiation, the social planner will observe increases in demand and overall social welfare. Our results also show that business practitioners could profit from privacy customization. (shrink)

Connected vehicle fleets have formed significant component of industrial internet of things scenarios as part of Industry 4.0 worldwide. The number of vehicles in these fleets has grown at a steady pace. The vehicles monitoring with machine learning algorithms has significantly improved maintenance activities. Predictive maintenance potential has increased where machines are controlled through networked smart devices. Here, benefits are accrued considering uptimes optimization. This has resulted in reduction of associated time and labor costs. It has also provided significant increase (...) in cost benefit ratios. Considering vehicle fault trends in this research predictive maintenance problem is addressed through hybrid deep learning-based ensemble method (HDLEM). The ensemble framework which acts as predictive analytics engine comprises of three deep learning algorithms viz modified cox proportional hazard deep learning (MCoxPHDL), modified deep learning embedded semi supervised learning (MDLeSSL) and merged LSTM (MLSTM) networks. Both sensor as well as historical maintenance data are collected and prepared using benchmarking methods for HDLEM training and testing. Here, times between failures (TBF) modeling and prediction on multi-source data are successfully achieved. The results obtained are compared with stated deep learning models. This ensemble framework offers great potential towards achieving more profitable, efficient and sustainable vehicle fleet management solutions. This helps better telematics data implementation which ensures preventative management towards desired solution. The ensemble method's superiority is highlighted through several experimental results. (shrink)

In this position paper, we would like to promote the alternative approach positioned between the two extreme positions consisting in refusing any innovation or in adopting technology without questioning it. This approach proposes a reflexive and responsible innovation based on a compromise between industrial and economic potentialities and a common respect of our human rights and values. We argue that the “silence of the chips right” is timely, relevant and sustainable to face ethical challenges raised by IoT such as protecting (...) privacy, trust, social justice, autonomy or human agency. We believe this technical solution may support establishing an ethics of IoT embedded in the technology itself. Our position is not ‘technocratic’: we do not agree with discourses arguing technology can fix problems. Through the responsible research and innovation approach we promote the idea that only human agency and user empowerment constitute a valid answer to the ethical, legal and social issues raised by IoT. (shrink)

In this paper, the Internet of Things with intelligent face perception and processing function is used to supervise online English teaching. In the intelligent learning environment, learners mainly learn by watching the information presentation screen of the learning content, i.e., the learning screen, which is the main environment for learners to learn and is the main channel for information interaction between learners and the learning content. The color matching, layout, graphic decoration, and background texture of the learning screen have a (...) significant impact on learners’ emotions, interests, motivation, and effect in the learning process. On the contrary, the accurate identification of learners’ emotions is the basis for building a harmonious emotional interaction in the wisdom learning environment and is an important means to judge learners’ learning status, which is of great significance to promote learners’ wisdom learning. In addition to providing learners with personalized learning contents and learning paths, the learning images presented by the intelligent learning environment should also be compatible with learners’ emotional states and visual emotional preferences and can play a role in regulating and stimulating learners’ learning emotions. The system works well in the testing process, which verifies the feasibility, rationality, and effectiveness of our application of face perception to online teaching effectiveness monitoring, and can be combined with the old result-oriented effectiveness monitoring method for online teaching, with certain theoretical research significance and practical application value. (shrink)

This paper aims to enhance security in IoT device networks through a visual tool that utilizes three projection techniques, including Beta Hebbian Learning (BHL), t-distributed Stochastic Neighbor Embedding (t-SNE) and ISOMAP, in order to facilitate the identification of network attacks by human experts. This work research begins with the creation of a testing environment with IoT devices and web clients, simulating attacks over Message Queuing Telemetry Transport (MQTT) for recording all relevant traffic information. The unsupervised algorithms chosen provide a set (...) of projections that enable human experts to visually identify most attacks in real-time, making it a powerful tool that can be implemented in IoT environments easily. (shrink)

In the modern business environment, characterized by rapid technological advancements and globalization, abetted by IoT and Industry 5.0 phenomenon, innovation is indispensable for competitive advantage and economic growth. However, many organizations are facing problems in its true implementation due to the absence of a practical innovation management framework, which has made the implementation of the concept elusive instead of persuasive. The present study has proposed a new innovation management framework labeled as “Absolute Innovation Management (AIM)” to make innovation more understandable, (...) implementable, and part of the organization’s everyday routine by synergizing the innovation ecosystem, design thinking, and corporate strategy to achieve competitive advantage and economic growth. The current study used an integrative literature review methodology to develop the “Absolute Innovation Management” framework. The absolute innovation management framework links the innovation ecosystem with the corporate strategy of the firm by adopting innovation management as a strategy through design thinking. Thus, making innovation more user/human-centered that is desirable by the customer, viable for business and technically feasible, creating both entrepreneurial and customer value, and boosting corporate venturing and corporate entrepreneurship to achieve competitive advantage and economic growth while addressing the needs of IoT and Industry 5.0 era. In sum, it synergizes innovation, design thinking, and strategy to make businesses future-ready for IoT and the industry 5.0 revolution. The present study is significant, as it not only makes considerable contributions to the existing literature on innovation management by developing a new framework but also makes the concept more practical, implementable and part of an organization’s everyday routine. (shrink)

The evolution of wireless communications, from the first to the fifth generation, has driven Internet of Things (IoT) advancements. IoT is transforming sectors like agriculture, healthcare, and transportation, but also presents challenges like spectrum bandwidth demand, speed requirements, and security issues. IoT environments, with embedded sensors and actuators, connect to other devices to transmit and receive data over the internet. These data are processed locally or in the cloud, enabling decision-making and automation. Various wireless technologies, including Bluetooth, Zigbee, LoRa, and (...) WiFi, cater to specific IoT applications. 5G, with its high speeds, low latency, and efficient bandwidth sharing, is ideal for high-speed data transmission, and thus it provides robust infrastructure for low-latency and bandwidth-sensitive applications. This latest mobile network technology is being rapidly implemented worldwide, providing unprecedented throughput and low latency, which are crucial for the IoT. This paper presents a comprehensive systematic review on 5G security features, vulnerabilities, threats to mobile devices, security in IoT devices, common attacks to IoT devices and protection of data in this environment. Despite enhanced security, 5G faces challenges like Distributed Denial of Service (DDoS), Man In The Middle (MITM), cross-slice disruptions, and side-channel attacks. (shrink)

It is now a common belief that the truths of our lives are hidden in the databases streamed from our interactions in smart environments. In this current hype of big data, the Internet of Things has been suggested as the idea to embed small sensors and actuators everywhere to unfold the truths beneath the surfaces of everything. However, remaining the technology that promises more than it can provide thus far, more important for the IoT’s actual expansion to various social domains (...) than the actual discovery of hidden truths has been people’s speculations about the unknown problems, such as hidden security issues or lifestyle concerns, beyond the narrow human knowability but assumed to leave their traces in the IoT-collected big data. This paper discuss this speculation as the concealed cognitive labor of IoT users that projects some fictitious values to the big data IoT companies accumulate. By the term pan-kinetics, the systemic operation of smart actuators is analyzed as the process through which fictitious values of data are converted to the real values as these actuators draw some profitable correlations from physical domains of the IoT. Analyzing smart electroencephalogram headsets as the unique IoT devices operating on human brains, it argues how the IoT translates this speculative realism of unknown problems into its big data, which the IoT developers believe to be full of machine-learnable correlations that would lead to the smart solutions of the problems. (shrink)

Arrhythmias are irregular heartbeats that may be life-threatening. Proper monitoring and the right care at the right time are necessary to keep the heart healthy. Monitoring electrocardiogram patterns on continuous monitoring devices is time-consuming. An intense manual inspection by caregivers is not an option. In addition, such an inspection could result in errors and inter-variability. This article proposes an automated ECG beat classification method based on deep neural networks to aid in the detection of cardiac arrhythmias. The data collected by (...) an Internet of Things enabled ECG monitoring device are transferred to a server. They are analysed by a deep learning model, and the results are shared with the primary caregiver. The proposed model is trained using the MIT-BIH ECG arrhythmia database to classify into four classes: normal beat, left bundle branch block beat, right bundle branch block beat, and premature ventricular contraction. The received data are sampled with an overlapping sliding window and divided into an 80:20 ratio for training and testing, with tenfold cross-validation. The proposed method achieves higher accuracy with a simple model without any preprocessing when compared with previous works. For the train and test sets, we achieved accuracy rates of 99.09 and 99.03%, respectively. A precision, recall, and F1 scores of 0.99 is obtained. The proposed model achieves its goal of developing a simple and accurate ECG monitoring system with improved performance. This simple and efficient deep learning approach for heartbeat classification could be applied in real-time telehealth monitoring systems. (shrink)

IoT connects devices, humans, places, and even abstract items like events. Driven by smart sensors, powerful embedded microelectronics, high-speed connectivity and the standards of the internet, IoT is on the brink of disrupting today’s value chains. Big Data, characterized by high volume, high velocity and a high variety of formats, is a result of and also a driving force for IoT. The datafication of business presents completely new opportunities and risks. To hedge the technical risks posed by the interaction between (...) “everything”, IoT requires comprehensive modelling tools. Furthermore, new IT platforms and architectures are necessary to process and store the unprecedented flow of structured and unstructured, repetitive and non-repetitive data in real-time. In the end, only powerful analytic tools are able to extract “sense” from the exponentially growing amount of data and, as a consequence, data science becomes a strategic asset. The era of IoT relies heavily on standards for technologies which guarantee the interoperability of everything. This paper outlines some fundamental standardization activities. Big Data approaches for real-time processing are outlined and tools for analytics are addressed. As consequence, IoT is a evolutionary process whose success in penetrating all dimensions of life heavily depends on close cooperation between standardization organizations, open source communities and IT experts. (shrink)

The Internet of Things (IoT) is an emerging global infrastructure that employs wireless sensors to collect, store, and exchange data. Increasingly, applications for marketing and advertising have been articulated as a means to enhance the consumer shopping experience, in addition to improving efficiency. However, privacy advocates have challenged the mass aggregation of personally-identifiable information in databases and geotracking, the use of location-based services to identify one’s precise location over time. This paper employs the framework of contextual integrity related to privacy (...) developed by Nissenbaum (Privacy in context: technology, policy, and the integrity of social life. Stanford University Press, Stanford, 2010) as a tool to understand citizen response to implementation IoT-related technology in the supermarket. The purpose of the study was to identify and understand specific changes in information practices brought about by the IoT that may be perceived as privacy violations. Citizens were interviewed, read a scenario of near-term IoT implementation, and were asked to reflect on changes in the key actors involved, information attributes, and principles of transmission. Areas where new practices may occur with the IoT were then highlighted as potential problems (privacy violations). Issues identified included the mining of medical data, invasive targeted advertising, and loss of autonomy through marketing profiles or personal affect monitoring. While there were numerous aspects deemed desirable by the participants, some developments appeared to tip the balance between consumer benefit and corporate gain. This surveillance power creates an imbalance between the consumer and the corporation that may also impact individual autonomy. The ethical dimensions of this problem are discussed. (shrink)

The Internet of Things (IoT) applied to intelligent transport systems has become a key element for understanding the way traffic flow behaves in cities, which helps in decision-making to improve the management of the transport system by monitoring and analyzing network traffic in real time, all with the aim of daily benefiting users of the city’s road infrastructure. Traffic volume estimation in real time, with high effectiveness, may help mobility management and improve traffic flow. Moreover, machine-learning algorithms have shown effectiveness (...) in various scientific fields and have provided a significant platform for achieving intelligent applications. Therefore, we applied various machine learning algorithms to classify the vehicular traffic status in the traffic network of two cities with more than 2 million inhabitants. It was first necessary to establish, from the attributes provided by the datasets, the object class from the LOS (Level of Services) thresholds proposed by the National Academies of Sciences, Engineering, and Medicine, for the basic segments of highways in an urban area. We then selected the attributes of interest using the Recursive Feature Elimination Method (RFE) to reduce the dimensionality of the data, and applied the DT, RF, ET, KNN, and MLP algorithms to train and classify the level of vehicular congestion, defining various volumes of training and validation data. The results show the high effectiveness of the algorithms, highlighting the MLP algorithm as the one that provides the highest effectiveness on average for the evaluated datasets, with a mean precision of 99.5%. (shrink)

The conjunction of wireless computing, ubiquitous Internet access, and the miniaturisation of sensors have opened the door for technological applications that can monitor health and well-being outside of formal healthcare systems. The health-related Internet of Things (H-IoT) increasingly plays a key role in health management by providing real-time tele-monitoring of patients, testing of treatments, actuation of medical devices, and fitness and well-being monitoring. Given its numerous applications and proposed benefits, adoption by medical and social care institutions and consumers may be (...) rapid. However, a host of ethical concerns are also raised that must be addressed. The inherent sensitivity of health-related data being generated and latent risks of Internet-enabled devices pose serious challenges. Users, already in a vulnerable position as patients, face a seemingly impossible task to retain control over their data due to the scale, scope and complexity of systems that create, aggregate, and analyse personal health data. In response, the H-IoT must be designed to be technologically robust and scientifically reliable, while also remaining ethically responsible, trustworthy, and respectful of user rights and interests. To assist developers of the H-IoT, this paper describes nine principles and nine guidelines for ethical design of H-IoT devices and data protocols. (shrink)

The Internet of Things (IoT) is, in part, an information handling system that can remove humans from the information handling process. The particular problem explored is how we are to understand privacy when considering informational systems that handle personal information in ways that impact people’s lives when there is no human operator in direct contact with that personal information. I argue that these new technologies need to take concepts like privacy into account, but also, that we ought also to take (...) these technologies into account to reconsider and perhaps reconceptualise privacy. This paper argues that while an inhuman system like the IoT does not necessarily violate the interpersonal privacy of people, if the IoT is used as part of a state surveillance program, a political notion of privacy may be violated. (shrink)

This chapter argues that the choice of trust conceptualisations in the context of consumer Internet of Things (IoT) can have a significant impact on the understanding and implementations of a user’s private data protection. Narrow instrumental interpretations of trust as a mere precondition for technology acceptance may obscure important moral issues such as malleability of user’s privacy decisions, and power imbalances between suppliers and consumers of technology. A shift of focus in policy proposals from trust to the trustworthiness of technology (...) can be the first step on the way to addressing these moral concerns. It is argued that complexity of IoT systems, comprised of technological artefacts and institutional data-collecting entities, warrants the moral value of distrust as a prima facie assumption for technological design and regulatory measures. Such a conceptual perspective highlights importance of technological measures that can minimise reliance on trust in consumer IoTs and regulatory measures aimed to improve transparency of IoT architectures. (shrink)

Even though public awareness about privacy risks in the Internet is increasing, in the evolution of the Internet to the Internet of Things these risks are likely to become more relevant due to the large amount of data collected and processed by the “Things”. The business drivers for exploring ways to monetize such data are one of the challenges identified in this paper for the protection of Privacy in the IoT. Beyond the protection of privacy, this paper highlights the need (...) for new approaches, which grant a more active role to the users of the IoT and which address other potential issues such as the Digital Divide or safety risks. A key facet in ethical design is the transparency of the technology and services in how that technology handles data, as well as providing choice for the user. This paper presents a new approach for users’ interaction with the IoT, which is based on the concept of Ethical Design implemented through a policy-based framework. In the proposed framework, users are provided with wider controls over personal data or the IoT services by selecting specific sets of policies, which can be tailored according to users’ capabilities and to the contexts where they operate. The potential deployment of the framework in a typical IoT context is described with the identification of the main stakeholders and the processes that should be put in place. (shrink)

The internet of things is increasingly spreading into the domain of medical and social care. Internet-enabled devices for monitoring and managing the health and well-being of users outside of traditional medical institutions have rapidly become common tools to support healthcare. Health-related internet of things (H-IoT) technologies increasingly play a key role in health management, for purposes including disease prevention, real-time tele-monitoring of patient’s functions, testing of treatments, fitness and well-being monitoring, medication dispensation, and health research data collection. H-IoT promises many (...) benefits for health and healthcare. However, it also raises a host of ethical problems stemming from the inherent risks of Internet enabled devices, the sensitivity of health-related data, and their impact on the delivery of healthcare. This paper maps the main ethical problems that have been identified by the relevant literature and identifies key themes in the on-going debate on ethical problems concerning H-IoT. (shrink)

The Fourth Industrial Revolution has become a global buzz word since the World Economic Forum adopted it as an annual issue in 2016. It is represented by hyper automation and hyper connectivity based on artificial intelligence, big data, robotics, and Internet of things. AI, big data, and robotics can contribute to developing hyper automation that can increase productivity and intensify industrial production. Particularly, robots using AI can make decision by themselves as human being on complicated processes. Along with the hyper (...) automation, the hyper connectivity increases not only at national, but also global level by using information and communication technologies. IoT is the core technology to create the hyper connectivity in Cyber Physical System that connects technology, nature, and human being. Accordingly, a perfect convergence between ICT and manufacturing can be completed in the Fourth Industrial Revolution era and an extremely efficient flexible production system by spreading IoT in CPS will be established. Under such a condition, innovative clusters must play their traditional roles in cradles of technology innovation and commercialization. It must be difficult challenges for innovative clusters to meet their targets and to be adjusted by the changing new environment at the same time. This paper argues how the Fourth Industrial Revolution can change the global production chain and how core technologies function in industries. Furthermore, it focuses on how innovative clusters have to evolve to respond the Fourth Industrial Revolution. Last, but not least it also analyzes whether or not innovative clusters can play their roles as technology innovation hubs in the real world and CPS in the Fourth Industrial Revolution era. (shrink)