Computational notebooks to support developers in prototyping IoT systems

LoRaWAN based internet of things (IoT) system for precision irrigation in plasticulture fresh-market tomato

Herein, an Internet of Things (IoT) system with remote reconfigurable wireless sensor network (WSN) nodes is presented and its application to measure group work activity in a classroom is discussed. This IoT system consists of wiki pages, bots, (defined as remotely controlled devices), gateways, and remotely reconfigurable WSN Nodes. The bots/gateways and WSN nodes of the IoT system are controlled by scripts written on wiki pages that are read by the bot/gateways, which then forward the commands contained in the scripts to the WSN nodes. Each WSN node then executes the commands, obtains the resulting sensor values, and then returns those values to the bot/gateways. The bot/gateways relay the values and write them onto the wiki page. Each WSN node is flexible and reconfigurable because its behavior can be changed by the script commands written onto the wiki page. Using this IoT system, we created a measurement system to evaluate activity levels of group work in a classroom. After developing the measurement system, we found it was possible to adjust the sampling rate for obtaining sensor values simply by rewriting the script on the wiki page without directly manipulating the WSN.

Privacy preservation in blockchain based IoT systems: Integration issues, prospects, challenges, and future research directions

Internet of Things (IoT) systems are characterized by being highly heterogeneous, distributed, and scalable, made up of a variety of devices that operate in uncertain and ubiquitous settings. In this sense, models@runtime emerges as a promising software development approach to address IoT systems’ intrinsic characteristics. This study presents a systematic review to know the state of the art using of models@runtime to support IoT systems’ operation. The methodology proposed by Kitchenham has been used to carry out this research. The systematic review answers the following research questions: i) How are models@runtime being used in the IoT domain? And ii) How is addressed the research in studies related to the use of models@runtime in the IoT domain? Initially, 692 primary studies were retrieved, where 50 relevant studies related to approaches based on models@runtime for IoT were selected after applying the corresponding inclusion and exclusion criteria. Those primary studies were classified based on the extraction criteria. Among review’s main results are that the models@runtime have been widely used to support the monitoring and self-adaptation mechanisms in IoT systems, as opposed to the few studies found aimed at interoperability, quality assurance, self-organization, and self-optimization of IoT systems, consisting of essential research opportunities.

A survey of trust computation models for service management in internet of things systems

This chapter discusses the architecture of Internet of Things (IoT) systems. IoT system security takes a team of experts in network security, computer security, hardware and software security, cloud infrastructure security, secure protocols, and cryptography. The security of an IoT system is extremely complex and crosses many security disciplines. Various industries and standards groups have developed and proliferated system architectures in order to better communicate the issues and requirements relating to systems for which they are concerned. The Internet of Things community is no different from any other architectural community. The primary difference is that IoT spans many different industries and ecosystems, and has a diverse set of concerns. The cloud is essential to an IoT system because it houses centralized applications and contains the data model of the IoT system, making those applications accessible to its users wherever they are, and is wholly independent of the actual location of the IoT devices themselves.

The purpose of this paper is to explore the role of Machine Learning (ML) in fortifying the security of cloudbased Internet of Things (IoT) systems, using a comprehensive security management approach. The methodological approach involved comparing different ML techniques such as Decision Trees, Random Forest, Support Vector Machines, and Convolutional Neural Networks. Their effectiveness was evaluated based on the accuracy of threat detection in cloud-based IoT systems. The findings revealed that Convolutional Neural Networks demonstrated the highest accuracy rate (98%) in threat detection, thereby significantly enhancing the security of IoT systems. It also identified improvements in threat detection, prevention, response, and system recovery across all ML techniques. Research limitations were primarily the rapidly evolving nature of both ML and IoT technologies, necessitating continual reassessments. The scope was also limited to cloud-based IoT systems, leaving room for further research on other types of IoT systems. The practical implications included improved system security, which could lead to increased trust and wider adoption of IoT technology in various sectors, from healthcare to home security. The social implications entail a safer digital environment, contributing to data privacy and reducing the risk of cyber threats for individuals and communities. The originality of this paper lies in its comprehensive approach to IoT security management using ML, providing valuable insights into the effectiveness of different ML techniques in enhancing threat detection accuracy.

Advanced digital signatures for preserving privacy and trust management in hierarchical heterogeneous IoT: Taxonomy, capabilities, and objectives

Wireless communication in Internet of Things (IoT) systems involves several devices communicating in the limited available frequency spectrum using different wireless communication standards. To achieve efficient spectrum usage in the IoT systems, it is desired to have the ability of dynamic spectrum allocation. Cognitive radios (CR) enable efficient spectrum utilization by performing spectrum sensing to gain the knowledge of current spectrum occupancy and dynamically reconfiguring the communication parameters, making them highly suitable for IoT systems. In this paper, we present the efficient hardware implementation of a spectrum sensing scheme for CR based IoT applications that require large bandwidth. We show that the proposed implementation on field programmable gate arrays (FPGAs) can achieve over 1.56x improvement in performance, while consuming 77% less generic resources and at a fractionally higher power consumption.

This paper presents an implementation of a Wireless Internet of Things (IoT) system applied to the traction motor drive condition monitoring in electric vehicles (EVs). The design and testing of the prototype using an ESP8266 microcontroller module to acquire motor's vibration, current, and temperature information for the motor condition monitoring application is presented. This IoT system has been designed and developed from the ground up using commercially off-the-shelf components and open-source software platform for fast, reliable data acquisitions, low power consumption, and data gathered by the IoT system get reported to the cloud server in real time. The experimental results reveal that the IoT system is capable of capturing and reporting vital motor's parameters to cloud server and an automatic notification is sent to operators when motor's abnormality is detected in real time. Thanks to IoT technology, the preventive maintenance of traction motor can be effectively and remotely planned with rich data collection and analysis. With advanced power consumption reduction techniques, a sensor node consumes extremely low amount of battery power at which ideal for mobile applications.

Developing Internet of Things (IoT) systems is not trivial and needs to be performed systematically to derive an IoT system that meets the required functional and non-functional concerns. Since IoT is applied to different heterogeneous domains usually a one-size-fits-all method is less feasible. For some cases a lightweight method with a few method artefacts are sufficient while in other cases a detailed set of method artefacts over the whole lifecycle might be required. So far, a few IoT system development methods (SDM) have been provided that include the steps necessary for guiding the development of IoT systems but these do not explicitly consider the situational needs for the required IoT method. In this paper we propose a situational method engineering (SME) approach for developing a method base that includes a broad set of method fragments which can be reused to develop customized methods. We illustrate the development of the method base using the existing IoT methods that have been proposed in the literature so far. Further we show how the method base can be used to develop methods for two different cases.

Door security system wherever needed, because to protect the parts that are stored, whether in housing, warehousing, offices, or in the industrial world. Security system currently developing digitally based is by using the Internet of Things (IoT) system. Microcontrollers, HC05 Bluetooth modules and RFID modules based IoT make it possible to be a door guard. The current problem is that even though the door is locked, it still occurs theft, and assume that the cost of making security is too expensive. Solution to the problem it is making RFID and Bluetooth-based door security control prototypes with the IoT system. The purpose of this study is to make a prototype of door security control devices based RFID and Bluetooth with an IoT system. For access to the door using an ID card and Smartphone. The method used is laboratory experiments. This research produces a prototypes of door security control devices versatile based IoT RFID and Bluetooth, at a cost cheap, economical, and effective to use. Keywords: Arduino, HC05, RFID, Servo Motor, LCD

PurposeThe purpose of this paper is to answer “Why do Chinese consumers use IOT systems?” and “Do consumers’ cognitive and affect experiences moderate the relationship between psychological perception factors and perceived usefulness?”Design/methodology/approachIn-depth interview with consumers and experts had been conducted and then the perceived psychological factors that influence perceived usefulness had been summarized. Based on a survey test of 337 smart home users, this study applies partial least squares technique analysis to test the research model.FindingsThe research results show that perceived psychological factors (perceived ease of use, perceived intelligence, perceived convenience and perceived privacy risk) have significant effect on the intention and behavior of IOT systems usage through perceived usefulness. Cognitive experience moderates the relationship between perceived ease of use and perceived usefulness, perceived privacy risk and perceived usefulness; affect experience moderates the relationship between perceived ease of use and perceived usefulness.Research limitations/implicationsThe current study mainly tested the antecedents of consumers’ usage of IOT systems, and the outcome of using the system was not investigated. Future research can examine the outcome (e.g. satisfaction, perceived value) by using the expectation-confirmation theory.Originality/valueThis study provides a useful insight into the key driving factors in consumers’ intention and behavior of using IOT systems. The previous studies over IOT systems have not observed consumers’ perception of IOT systems, but in fact IOT systems are being applied to more and more personal users.

Since the Internet of Things (IoT) will be entwined with everything we use in our daily life, the consequence of security flaws escalates. Smart objects will govern most of the home appliances and car engines yielding potential disaster scenarios. In this context, successful attacks could lead to chaos and scary scenarios (www.darkreading.com). Unprotected personal information may expose sensitive and embarrassing data to the public and attacks may threaten not only our computers and smart devices, but our intimacy and perhaps our lives too. Because persons and objects will be bonded with each other, user consent becomes critical. Therefore, thing, object, and user Identity will be the focus of future IoT security solutions, yielding a Trust, Security, and Privacy (TSP) paradigm, which may constitute the Achilles' heel of IoT. While security issues are quite straightforward, mainly from background knowledge, privacy issues are far more complex. Privacy constitutes a rather challenging task, even for the m...

Small printed antennas suffer from low efficiency. Low profile efficient antennas are crucial in the development of commercial compact 5G communication and Internet of things (IOT) systems. The communication, IOT and biomedical industries have been in rapid growth in recent years. It is important to develop efficient high gain compact antennas for 5G communication and IOT systems. Metamaterials and fractal structures may be used to improve the efficiency of compact printed antennas. In this chapter metamaterial antennas will be presented. Metamaterial technology is used to design small wideband wearable antennas with high efficiency. Design considerations and the computed and measured results of printed metamaterial antennas with high efficiency are presented in this chapter. The proposed antenna may be used in communication and medical systems. The antennas’ S11 results for different positions on the human body are presented in this chapter. The gain and directivity of the patch antenna with split ring resonator (SRR) is higher by 2.5 dB than the patch antenna without SRR. The resonant frequency of the antenna with SRR on human body is shifted by 3%.