Internet Of Things Solutions Research Articles

Разработка архитектурного решения программного обеспечения для устройств интернет-вещей

The article presents the development of an architectural software solution for Internet of Things (IoT) devices that implements the functionality of an automatic medical drug dispenser, based on the ESP32 hardware platform and utilizing the capabilities of the existing real-time operating systems (RTOS). The software architecture for IoT devices was designed with scalability and fault tolerance in mind. All components of the system interact with each other through asynchronous callback functions, which provides flexibility and extensibility to the architecture. Testing for system fault tolerance was conducted. The architecture can be implemented and used as the basis for any IoT device, allowing for support of modern security and functionality stacks, by implementing this functionality once in any of the devices. The process of designing the software architecture is presented, including the selection of suitable technologies and libraries. Particular attention was paid to ensuring the safety and reliability of the device, including protection against an unauthorized access and errors in operation. The experimental results show high efficiency and accuracy of the automatic medical drug dispenser based on the developed software. The practical part provides examples of implementing the proposed architecture in the C and C++ languages, with examples and basic interaction diagrams between the components. The rxcpp library was also used in writing the C++ implementation, which made it easier to write the code base for interacting with the operating system resources and reusing the multithreaded interaction with the system.

Simulation Studies of Link Group in Elastic Optical Networks Used in Internet of Things Solutions

Abstract The elastic optical network (EON) solution is the most flexible in terms of allocation of resources for various traffic streams transported in core part (edge-cloud) of Internet of Things (IoT) networks. This paper presents the results of a study on the determination of the occupancy distribution and the loss probability for particular traffic flows offered in EONs supporting IoT systems. The purpose of the research was to determine the impact of: the number of links making up a group, the numbers of frequency slot units (FSUs) in individual EON link, the traffic intensity of individual traffic flows, the capacity of the EON link (number of FSUs) and the number of FSUs requested by different traffic streams. The developed simulation program of link group of EON allows the calculation of the values of the occupancy distribution and loss probability. The results obtained from the simulation are presented on the graphs in the form of points with confidence intervals.

RIS-Assisted Ambient Backscatter Communication for SAGIN IoT

The space, air and ground integrated network (SAGIN) will greatly promote the development of the Internet of Things (IoT). Green IoT will be an important part of SAGIN. Ambient backscatter communication (AmBC) is a potential solution for green SAGIN IoT. To improve the achievable sum rate (ASR) of the AmBC system, we propose a reconfigurable intelligent surface (RIS) assisted AmBC system. In the single-BD AmBC scenario, we firstly give the phase shifts that maximize the gain of the reflection link of the AmBC system, and then give the optimal reflection coefficient. The proposed scheme does not need to solve the convex semidefinite program (SDP) problem, and has the characteristics of low computational complexity. In the multi-BD AmBC scenario, we first propose a multi-BD phase shifts initialization strategy to ensure the stability of the proposed scheme. Then, we give the optimal reflection coefficient and phase shifts based on iterative method. Simulations show that the RIS-assisted AmBC scheme is superior to the non-RIS-assisted AmBC scheme.

Unveiling the Internet of Things (IoT) Applications in Aquaculture: A Survey and Prototype Design with ThingSpeak Analytics

The study examines the potential impact of IoT in aquaculture, and its role in enhancing water quality monitoring as well as the disease prevention. It highlights the transformative power of IoT technology in providing real-time data on water parameters and enabling proactive measures against diseases. The study emphasizes the significance of adopting IoT solutions to optimize water conditions, mitigate disease risks, and enhance fish health. It also explores recent advancements, key challenges, and future directions in IoT applications for aquaculture, including water quality monitoring, feed automation systems, environmental control systems, fish tracking and monitoring systems, remote monitoring and control systems, smart harvesting systems, and disease detection and prevention systems. Based on a comprehensive literature survey, this paper introduces a research proposal focusing on water quality monitoring and disease prevention in fish. The progress thus far encompasses the selection of hardware components, sensor testing, and ongoing activities in programming and debugging.

An energy-efficient and reliable data gathering infrastructure using the internet of things and smart grids

Introduction: The Internet of Things (IoT) and Smart Grids (SGs) growth results from the advancement of computer hardware and ubiquitous computation for energy-efficient and reliable data gathering. Background: The limitations of the present cloud computing framework in energy systems remain unresolved, such as fully recognizing the requisites of high data usage with low latency which is discussed for a cloud computing scheme in IoT-based smart power stations. Problem Statement: IoT growth results from the advancement of computer hardware and ubiquitous computation. Among the various IoT solutions, SGs stand out because they combine several embedded smart techniques to increase the security and dependability of electricity grids. Methodology: A Particle Swarm Optimization based energy efficient integration of Smart Grid (PSO-SG) is designed using IoT. Modern technology establishes a novel hardware and software architecture and integrates cloud services into the cloud-based electricity network. Findings: As a result, a sizable amount of data produced by the electricity network will be examined, handled, and saved at the network. IoT-based power systems will enable the interconnection and administration of large endpoint devices, offer real-time evaluation and treatment of vast data, and promote the modernization of the power grid with the help of the cloud computing model.

Blockchain-Empowered Security Enhancement IoT Framework in Building Management System

Centralized architectures, like the cloud model, have their advantages, but they also come with drawbacks, such as higher upfront costs, longer deployment times, and a higher probability of catastrophic failure. Building Management Systems (BMS) is an application that can adopt Internet of Things (IoT) designs and services. However, implementing IoT in a highly modular environment with various moving parts and interdependencies between stakeholders can create security issues. Therefore, this paper proposes a system design using Blockchain technology as a means to protect and control the system, which includes the integration of IoT and BMS technologies. This paper has also included broad discussion on current Blockchain based IoT solution and its IoT limitations in Building Management Systems.

The Integration of Triboelectric Nanogenerators and Supercapacitors: The Key Role of Cellular Materials.

The growing demand for sustainable and efficient energy harvesting and storage technologies has spurred interest in the integration of triboelectric nanogenerators (TENGs) with supercapacitors (SCs). This combination offers a promising solution for powering Internet of Things (IoT) devices and other low-power applications by utilizing ambient mechanical energy. Cellular materials, featuring unique structural characteristics such as high surface-to-volume ratios, mechanical compliance, and customizable properties, have emerged as essential components in this integration, enabling the improved performance and efficiency of TENG-SC systems. In this paper, we discuss the key role of cellular materials in enhancing TENG-SC systems' performance through their influence on contact area, mechanical compliance, weight, and energy absorption. We highlight the benefits of cellular materials, including increased charge generation, optimized energy conversion efficiency, and adaptability to various mechanical sources. Furthermore, we explore the potential for lightweight, low-cost, and customizable cellular materials to expand the applicability of TENG-SC systems in wearable and portable devices. Finally, we examine the dual effect of cellular materials' damping and energy absorption properties, emphasizing their potential to protect TENGs from damage and increase overall system efficiency. This comprehensive overview of the role of cellular materials in the integration of TENG-SC aims to provide insights into the development of next-generation sustainable energy harvesting and storage solutions for IoT and other low-power applications.

Ivycide: Smart Intrusion Detection System Against E-IoT Driver Threats

The rise of Internet of Things (IoT) devices has led to the proliferation of smart environments worldwide. Although commodity IoT devices are employed by ordinary end-users, complex environments such as smart buildings, government, or private offices, or conference rooms require customized and highly reliable IoT solutions. Enterprise Internet of Things (E-IoT) connect such environments to the Internet and are professionally managed solutions usually offered by dedicated vendors As E-IoT systems require specialized training, closedsource software, and proprietary equipment to deploy. In effect, E-IoT systems present an unprecedented, under-researched, and unexplored threat vector for an attacker. In this work, we focus on E-IoT drivers, software modules used to integrate devices into E-IoT systems, as an attack mechanism. We first present PoisonIvy, a series of generalized proof-of-concept attacks used to demonstrate that an attacker can use a malicious driver to perform denial-of-service attacks, gain remote control, and abuse E-IoT system resources. To defend against E-IoT driverbased threats, we introduce IVYCIDE, a novel intrusion detection system used to detect unexpected E-IoT network traffic from an E-IoT system. IVYCIDE operates as a passive monitoring system within an E-IoT system using machine learning and signature-based classification to detect POISONIVY attacks. We evaluated the performance of IVYCIDE in a realistic E-IoT deployment. Our detailed evaluation results show that IVYCIDE achieves an average accuracy of 97% in classifying the type of POISONIVY attack and operates without modifications or operational overhead to existing E-IoT systems.

More than two decades of research on IoT in agriculture: a systematic literature review

PurposeAgriculture is one sector where the Internet of things (IoT) is expected to make a major impact. Yet, its adoption in the sector falls behind expectations. The purpose of this paper is to present the state-of-the-art of IoT in agriculture and investigate its slow adoption in the sector.Design/methodology/approachThe authors have undertaken a systematic review and a synthesis of 1355 relevant publications over the last decade.FindingsThis literature review reveals that the “big three” barriers for the overall sector are cost, skills and standardization. The lack of connectivity and data governance are two key reasons why most of the proposed IoT solutions are standalone systems of limited scope, while the majority of commercial IoT efforts focus on practices in the protected indoor environment. Lastly, the analysis of past research along the five layers of the IoT system architecture reveals limited attention to barriers and solutions at the business layer, which represents a research opportunity for information systems scholars.Research limitations/implicationsIt is possible that some of relevant publications were missed in the literature search, although the search queries were kept as broad as possible to avoid the exclusion of any relevant work. Any publication written in any other language other than English was excluded from the review. Given the geographical distribution of the reviewed English publications (see section 4.1), it is highly likely that important works written by Chinese and European scholars in their native language were overlooked.Practical implicationsThis study provides practical insights into the technical and organisational challenges on the ground. It is the hope that this literature review lays the groundwork for IS researchers who are well positioned to investigate technology adoption challenges in the relatively understudied agriculture sector.Originality/valueTo the best of the authors’ knowledge, this is the first comprehensive review of adoption barriers and solutions across all five layers of the IoT system architecture.

Bee colony remote monitoring based on IoT using ESP-NOW protocol.

Information and communication technologies, specifically the Internet of Things (IoT), have been widely used in many agricultural practices, including beekeeping, where the adoption of advanced technologies has an increasing trend. Implementation of precision apiculture methods into beekeeping practice depends on availability and cost-effectiveness of honey bee colony monitoring systems. This study presents a developed bee colony monitoring system based on the IoT concept and using ESP8266 and ESP32 microchips. The monitoring system uses the ESP-NOW protocol for data exchange within the apiary and a GSM (Global System for Mobile communication)/GPRS (General packet radio service) external interface for packet-based communication with a remote server on the Internet. The local sensor network was constructed in a star type logical topology with one central node. The use of ESP-NOW protocol as a communication technology added an advantage of longer communication distance between measurement nodes in comparison to a previously used Wi-Fi based approach and faster data exchange. Within the study, five monitoring devices were used for real-time bee colony monitoring in Latvia. The bee colony monitoring took place from 01.06.2022 till 31.08.2022. Within this study, the distance between ESP-NOW enabled devices and power consumption of the monitoring and main nodes were evaluated as well. As a result, it was concluded that the ESP-NOW protocol is well suited for the IoT solution development for honeybee colony monitoring. It reduces the time needed to transmit data between nodes (over a large enough distance), therefore ensuring that the measurement nodes operate in an even lower power consumption mode.

Determining Real-Time Communication Feasibility in IoT Systems Supported by LoRaWAN.

LoRaWAN is a long range and low power protocol devised for connecting devices under the Internet of Things (IoT) paradigm. This protocol was not conceived to support real-time message delivery; therefore, it is not always feasible using it to support IoT solutions involving large wireless sensors networks and time constraint messaging, e.g., in early warning systems for natural hazards, remote monitoring of industrial machinery or autonomous control of transportation systems. This paper presents a model that provides certainty, at the design time of IoT systems, about the real-time communication capability of their supporting network. It allows solution designers: (1) to decide if developing or not a real-time IoT solution based on the feasibility of its communication infrastructure, and (2) to improve the communication infrastructure to try making real-time communication feasible using LoRaWAN.

DIdM-EIoTD: Distributed Identity Management for Edge Internet of Things (IoT) Devices.

The Internet of Things (IoT) paradigm aims to enhance human society and living standards with the vast deployment of smart and autonomous devices, which requires seamless collaboration. The number of connected devices increases daily, introducing identity management requirements for edge IoT devices. Due to IoT devices' heterogeneity and resource-constrained configuration, traditional identity management systems are not feasible. As a result, identity management for IoT devices is still an open issue. Distributed Ledger Technology (DLT) and blockchain-based security solutions are becoming popular in different application domains. This paper presents a novel DLT-based distributed identity management architecture for edge IoT devices. The model can be adapted with any IoT solution for secure and trustworthy communication between devices. We have comprehensively reviewed popular consensus mechanisms used in DLT implementations and their connection to IoT research, specifically identity management for Edge IoT devices. Our proposed location-based identity management model is generic, distributed, and decentralized. The proposed model is verified using the Scyther formal verification tool for security performance measurement. SPIN model checker is employed for different state verification of our proposed model. The open-source simulation tool FobSim is used for fog and edge/user layer DTL deployment performance analysis. The results and discussion section represents how our proposed decentralized identity management solution should enhance user data privacy and secure and trustworthy communication in IoT.

Multihop Task Routing in UAV-Assisted Mobile-Edge Computing IoT Networks With Intelligent Reflective Surfaces

The cooperation between Unmanned Aerial Vehicles (UAVs) and ground Mobile Edge Computing (MEC) servers in processing tasks is becoming one of the main research trends of MEC networks. Despite the advantages of UAV-assisted MEC, it is restricted by the limited battery capacity and sensitive energy consumption of UAVs. Unlike the previous works where UAVs are allowed to either process tasks locally or offload them to ground MEC servers, in this paper, we propose a multi-hop task routing solution for Internet of Things (IoT) networks in which a UAV can also relay to another UAV with better connection to a ground MEC server. Furthermore, the UAV can make benefit of existing Intelligent Reflective Surfaces (IRSs) to further improve tasks offloading and reduce energy consumption. We show that the problem of minimizing the total energy of UAVs is NP-hard, and we propose a graph-based heuristic solution to solve it. Simulation results show that the proposed graph-based solution outperforms the traditional no UAV-UAV relaying scheme, especially when IRSs are deployed. Furthermore, a Convolutional Neural Network (CNN) is devised to reduce the delay of finding the decisions for the UAVs at the centralized coordinator. Simulations show that the CNN achieves very close energy consumption performance and a remarkable reduction in execution time compared to the graph-based heuristic solution.

Backscatter‐assisted Non‐orthogonal multiple access network for next generation communication

AbstractNon‐orthogonal multiple access (NOMA) technique introduces spectrum cooperation among different users and devices, which improves spectrum efficiency significantly. Energy‐limited devices benefit from the backscatter (BAC) technique to transmit signals without extra energy consumption. The combination of NOMA and BAC provides a promising solution for Internet of Things (IoT) networks, where massive devices simultaneously transmit and receive signals. This study investigates a system model with two NOMA downlink users and an uplink device. The aim is to maximise the data rate of the uplink device by optimising the power allocation coefficient and the backscattering coefficient. Meanwhile the quality of service requirements of two NOMA users are guaranteed. The closed‐form solution of two optimisation variables is derived, and an alternating algorithm is also proposed to solve the formulated optimisation problem efficiently. The proposed system verifies the feasibility of IoT devices being added into existing networks and provides a promising solution for wireless communication networks in the future.

Energy-Aware IoT-Based Method for a Hybrid On-Wrist Fall Detection System Using a Supervised Dictionary Learning Technique.

In recent decades, falls have posed multiple critical health issues, especially for the older population, with their emerging growth. Recent research has shown that a wrist-based fall detection system offers an accessory-like comfortable solution for Internet of Things (IoT)-based monitoring. Nevertheless, an autonomous device for anywhere-anytime may present an energy consumption concern. Hence, this paper proposes a novel energy-aware IoT-based architecture for Message Queuing Telemetry Transport (MQTT)-based gateway-less monitoring for wearable fall detection. Accordingly, a hybrid double prediction technique based on Supervised Dictionary Learning was implemented to reinforce the detection efficiency of our previous works. A controlled dataset was collected for training (offline), while a real set of measurements of the proposed system was used for validation (online). It achieved a noteworthy offline and online detection performance of 99.8% and 91%, respectively, overpassing most of the related works using only an accelerometer. In the worst case, the system showed a battery consumption optimization by a minimum of 27.32 working hours, significantly higher than other research prototypes. The approach presented here proves to be promising for real applications, which require a reliable and long-term anywhere-anytime solution.

Green IoT: A Review and Future Research Directions

The internet of things (IoT) has a significant economic and environmental impact owing to the billions or trillions of interconnected devices that use various types of sensors to communicate through the internet. It is well recognized that each sensor requires a small amount of energy to function; but, with billions of sensors, energy consumption can be significant. Therefore, it is crucial to focus on developing energy-efficient IoT technology and sustainable solutions. The contribution of this article is to support the implementation of eco-friendly IoT solutions by presenting a thorough examination of energy-efficient practices and strategies for IoT to assist in the advancement of sustainable and energy-efficient IoT technologies in the future. Four framework principles for achieving this are discussed, including (i) energy-efficient machine-to-machine (M2M) communications, (ii) energy-efficient and eco-sustainable wireless sensor networks (WSN), (iii) energy-efficient radio-frequency identification (RFID), and (iv) energy-efficient microcontroller units and integrated circuits (IC). This review aims to contribute to the next-generation implementation of eco-sustainable and energy-efficient IoT technologies.

Formal Analysis of Trust and Reputation for Service Composition in IoT

The exponential growth in the number of smart devices connected to the Internet of Things (IoT) that are associated with various IoT-based smart applications and services, raises interoperability challenges. Service-oriented architecture for IoT (SOA-IoT) solutions has been introduced to deal with these interoperability challenges by integrating web services into sensor networks via IoT-optimized gateways to fill the gap between devices, networks, and access terminals. The main aim of service composition is to transform user requirements into a composite service execution. Different methods have been used to perform service composition, which has been classified as trust-based and non-trust-based. The existing studies in this field have reported that trust-based approaches outperform non-trust-based ones. Trust-based service composition approaches use the trust and reputation system as a brain to select appropriate service providers (SPs) for the service composition plan. The trust and reputation system computes each candidate SP's trust value and selects the SP with the highest trust value for the service composition plan. The trust system computes the trust value from the self-observation of the service requestor (SR) and other service consumers' (SCs) recommendations. Several experimental solutions have been proposed to deal with trust-based service composition in the IoT; however, a formal method for trust-based service composition in the IoT is lacking. In this study, we used the formal method for representing the components of trust-based service management in the IoT, by using higher-order logic (HOL) and verifying the different behaviors in the trust system and the trust value computation processes. Our findings showed that the presence of malicious nodes performing trust attacks leads to biased trust value computation, which results in inappropriate SP selection during the service composition. The formal analysis has given us a clear insight and complete understanding, which will assist in the development of a robust trust system.

IoT solution for smart water distribution networks based on a low-power wireless network, combined at the device-level: A case study

Wireless systems enable the implementation and deployment of efficient Internet of Things (IoT) solutions in various applications such as smart cities, smart industry, smart transportation, or agriculture 4.0. The low power consumption of battery powered devices provides long system lifetime. Taking advantage of the energy consumption reduction mechanisms of the IEEE 802.15.4g and Narrowband IoT (NB-IoT) standards, this work develops a combined wireless network with application to smart metering for water distribution systems. The end devices used for reading water meters transmit their measurements through cluster heads with dual wireless connectivity. This combined network also finds application in other environments, such as industrial areas with a large geographical extension. Experimental results and simulations results obtained with two demonstrators show an estimate of battery life of more than a decade for those nodes with the highest power requirements.

A transformative shift toward blockchain‐basedIoTenvironments: Consensus, smart contracts, and future directions

AbstractRecently, Internet‐of‐Things (IoT) based applications have shifted from centralized infrastructures to decentralized ecosystems, owing to user data's security and privacy limitations. The shift has opened new doors for intruders to launch distributed attacks in diverse IoT scenarios that jeopardize the application environments. Moreover, as heterogeneous and autonomous networks communicate, the attacks intensify, which justifies the requirement of trust as a key policy. Recently, blockchain‐based IoT solutions have been proposed that address trust limitations by maintaining data consistency, immutability, and chronology in IoT environments. However, IoT ecosystems are resource‐constrained and have low bandwidth and finite computing power of sensor nodes. Thus, the inclusion of blockchain requires an effective policy design regarding consensus and smart contract environments in heterogeneous IoT applications. Recent studies have presented blockchain as a potential solution in IoT, but an effective view of consensus and smart contract design to meet the end application requirements is an open problem. Motivated by the same, the survey presents the integration of suitable low‐powered consensus protocols and smart contract design to assess and validate the blockchain‐IoT ecosystems. We present blockchain‐IoT's emerging communication and security aspects with performance issues of consensus protocols, interoperability, and implementation platforms. A case study of a smart contract‐based blockchain‐driven ecosystem is presented with a comparative analysis of mining cost and latency, which shows its suitability in real‐world setups. We also highlight attacks on blockchain IoT, open issues, potential findings, and future directions. The survey intends to drive novel solutions for future consensus and safe, smart contract designs to support applicative IoT ecosystems.

Monitoring and Control Framework for IoT, Implemented for Smart Agriculture.

To mitigate the effects of the lack of IoT standardization, including scalability, reusability, and interoperability, we propose a domain-agnostic monitoring and control framework (MCF) for the design and implementation of Internet of Things (IoT) systems. We created building blocks for the layers of the five-layer IoT architecture and built the MCF's subsystems (monitoring subsystem, control subsystem, and computing subsystem). We demonstrated the utilization of MCF in a real-world use-case in smart agriculture, using off-the-shelf sensors and actuators and an open-source code. As a user guide, we discuss the necessary considerations for each subsystem and evaluate our framework in terms of its scalability, reusability, and interoperability (issues that are often overlooked during development). Aside from the freedom to choose the hardware used to build complete open-source IoT solutions, the MCF use-case was less expensive, as revealed by a cost analysis that compared the cost of implementing the system using the MCF to obtain commercial solutions. Our MCF is shown to cost up to 20 times less than normal solutions, while serving its purpose. We believe that the MCF eliminated the domain restriction found in many IoT frameworks and serves as a first step toward IoT standardization. Our framework was shown to be stable in real-world applications, with the code not incurring a significant increase in power utilization, and could be operated using common rechargeable batteries and a solar panel. In fact, our code consumed so little power that the usual amount of energy was two times higher than what is necessary to keep the batteries full. We also show that the data provided by our framework are reliable through the use of multiple different sensors operating in parallel and sending similar data at a stable rate, without significant differences between the readings. Lastly, the elements of our framework can exchange data in a stable way with very few package losses, being able to read over 1.5 million data points in the course of three months.