Things IoTs Research Articles

Next-Generation Air Quality Monitoring For “Urban Environments”

Air quality monitoring in urban environments has become increasingly crucial due to rising pollution levels and its associated health risks. This paper explores the transformative potential of advance (Internet of Things) IOT solutions in urban air quality monitoring.

Synergistic photocatalytic breakdown of azo dyes coupled with H2 generation via Cr-doped α-Fe2O3 nanoparticles

This research addresses the scalable and inexpensive synthesis of α-Fe2O3via hydrothermal method without any precipitating agent as well as the enhancement of solar driven photocatalytic and H2 production through doping different chromium proportions. Competency of α-Fe2O3, both pure and doped with chromium, to function as photocatalyst was evaluated by its interaction with multiple dyes, which was real-time monitored utilizing (Internet of Things) IoT technique. By adding chromium, the rate of deterioration increased substantially from 15 to 94% for TB under sunlight in a remarkably brief 20 min by employing a very small amount of Cr0.8Fe1.2O3 (0.3 g/L), as evidenced by high degree of mineralization i.e. 85% and LC-HRMS. Also, the rapid breakdown of Trypan Blue (TB) was indicated by BOD5/COD ratio. Moreover, Cr-doped α-Fe2O3 displays excellent H2 production (~ 132 μmol h−1 g−1) as compared to α-Fe2O3. This work highlights the potential utilization of Cr-doped α-Fe2O3 for the purification of industrial waste water and green energy harvesting.

Internet of Things - Novel Application in Agriculture

Abstract: In the Present Era, the world is experiencing a strong rush towards modern technology, while specialized companies are living a terrible rush in the information and Communication technology towards the so-called Internet of things IoT or Internet of objects, which is the integration of things with the world of Internet, by adding hardware or/and software to be smart and so is able to communicate with each other and participate effectively in all aspects of daily life. By enabling new forms of communication between people and things, and between things themselves, that will change the traditional life into a high style of living. But it won’t be easy, because there are still many challenges and issues that need to be addressed and have to be viewed from various aspects to realize their full potential. The main objective of this paper is to provide the reader with a detailed discussion from a technological and social perspective. The various IoT aspects, definition and architecture, challenges and issues were discussed. Furthermore, a description of several sensors and actuators and their smart communication. Also, the most important application areas of IoT were presented with a case study. This work will help readers and researchers understand the IoT and its potential application in the real world

QoIoTX: A QoE-Aware IoT Service Discovery Framework

Quality of Experience QoE is a research area that evaluates performance based on subjective and objective metrics for the use of a product or a service. Currently, the substantial majority of QoE works mainly focus on multimedia services. However, the introduction of Internet of Things IoT has brought a new level of complexity into the field of QoE evaluation. With the evolution of new IoT technologies such as machine to machine communication and artificial intelligence, utilizing additional evaluation factors alongside the traditional ones is a crucial demand. This paper proposes QoIoTX, a QoE-based service discovery framework that can be utilized to evaluate the QoE of IoT service/application on the fly considering multiple parameters about data, network, users, and services. It extends the conventional QoE and goes beyond its legacy evaluation phases. Also, provides a novel alternative approach to evaluate the IoT services subjectively rather than using the traditional approaches that do not cope with the rapidly evolving services. Although each of the identified QoE factors is measured on a different scale and may involve different units of measurement, the proposed work can effectively evaluate the QoE through providing a single value that represents the acceptability degree of each service.

Systematic literature review: Digital twins' role in enhancing security for Industry 4.0 applications

AbstractConnectivity and data exchange are key features of Industry 4.0. In this paradigm, (Industrial) Internet of Things ((I)IoT) devices are a vital component facilitating the collection and transmission of environmental data from the physical system to the central station for processing and analysis (digital twin [DT]). However, although (I)IoT devices play a critical role in this process, they are not inherently equipped to run strong encryption mechanisms to secure the data they transmit over wired or wireless channels. This research aims to explore the potential of DTs in securing Industry 4.0 applications and the security mechanism employed to ensure confidentiality, integrity, and authentication of data communicated between (I)IoT and DT through a systematic literature review (SLR). This SLR, based on the analysis of 67 papers published between 2018 and 2023, underscores the evolving significance of DT technology, particularly within the ambit of Industry 4.0. The findings illuminate the pervasive influence of DT technology across multiple industrial sectors. The result SLR revealed that DT is growing and being widely adopted as a security tool particularly in Industry 4.0 using enabling technology like machine learning, data analytics, blockchain, and 5G networks to provide security solutions such as intrusion detection, vulnerability assessment, cyber range, and threat intelligence.

A Survey on IoT-Edge-Cloud Continuum Systems: Status, Challenges, Use Cases, and Open Issues

The rapid growth in the number of interconnected devices on the Internet (referred to as the Internet of Things—IoT), along with the huge volume of data that are exchanged and processed, has created a new landscape in network design and operation. Due to the limited battery size and computational capabilities of IoT nodes, data processing usually takes place on external devices. Since latency minimization is a key concept in modern-era networks, edge servers that are in close proximity to IoT nodes gather and process related data, while in some cases data offloading in the cloud might have to take place. The interconnection of a vast number of heterogeneous IoT devices with the edge servers and the cloud, where the IoT, edge, and cloud converge to form a computing continuum, is also known as the IoT-edge-cloud (IEC) continuum. Several key challenges are associated with this new computing systems’ architectural approach, including (i) the design of connection and programming protocols aimed at properly manipulating a huge number of heterogeneous devices over diverse infrastructures; (ii) the design of efficient task offloading algorithms aimed at optimizing services execution; (iii) the support for security and privacy enhancements during data transfer to deal with the existent and even unforeseen attacks and threats landscape; (iv) scalability, flexibility, and reliability guarantees to face the expected mobility for IoT systems; and (v) the design of optimal resource allocation mechanisms to make the most out of the available resources. These challenges will become even more significant towards the new era of sixth-generation (6G) networks, which will be based on the integration of various cutting-edge heterogeneous technologies. Therefore, the goal of this survey paper is to present all recent developments in the field of IEC continuum systems, with respect to the aforementioned deployment challenges. In the same context, potential limitations and future challenges are highlighted as well. Finally, indicative use cases are also presented from an IEC continuum perspective.

Connectivity in the era of the (I)IoT: about security, features and limiting factors of reconfigurable intelligent surfaces

What are the key drivers of the (Industrial) Internet of Things ((I)IoT)? Alongside the interconnection of the various devices, sensors, and actuators, it is above all the data collected and transmitted that is of particular significance, the (I)IoT itself is the source and recipient of various types of data. Within this, there are two main aspects that need to be considered: (i) the transmission of data with appropriate latency and reliability requirements, and (ii) the safeguarding of this data. Both requirements are taken into account during the development of the Sixth Generation (6G) Wireless Systems. This is conceived to deliver higher data rates, reduced cost deployment, and enhanced reliability while providing universal connectivity. Hence, to assist such a vast network domain, (new) 6G-enabling technologies are developed, which include Reconfigurable Intelligent Surfaces (RISs), that are capable of modifying and reconfiguring the wireless propagation channels. This work describes concepts on how security, in particular Physical Layer Security (PhySec) methods, can be supported by RISs. Furthermore, an effective impedance surface model is presented, allowing efficient simulation of beamsplitting and shaping properties of RISs. Finally, the applicability of the use cases is mentioned, with a particular focus on Visible Light Communication (VLC).

Alexa Enabled IoT Device Simulation Using C# And AWS Lambda

Purpose: Nowadays, device operation using voice commands is becoming popular. Several voice command services are available. Among them, Alexa from Amazon is the most popular. Almost Every day, vendors are integrating Alexa into their new products worldwide. We need physical devices for the device operation or understanding of the process flow of Alexa. Sometimes, physical devices are costly, or availability is poor. Here, we demonstrated how to create a simulated Alexa-enabled IoT device. We used several Amazon cloud services to execute the process flow. Alexa's skill is developed inside the Alexa developer console. To process the command, we use the AWS Lambda function. AWS IoT cloud service is used to trigger IoT devices over MQTT. For simulated devices, we are using a C# MQTT client. The researcher trying to simulate an Alexa-enabled device into their project can get some reference information from this work. Design/Methodology/Approach: We create a graphical user interface (GUI) to interact with the user or display the device's status. The GUI is connected with the C# AWS IoT Device Shadow client. We created IoT Things in the AWS cloud. Under the IoT Shadow, we created a Device shadow. The Alexa service triggers the lambda function. The Lambda function updates the Shadow register, which resides inside the cloud. The c# shadow client receives a notification when the device Shadow updates and updates the GUI element that represents the equipment. We can use any Alexa device to send voice commands, like the Alexa mobile app, Echo Dot, or Alexa PC app. Findings/Result: Through this research work, we created and tested virtual devices that can be experiments or research work using Alexa voice commands. It has been tested for a long time. It performed well, and no issue was found. Using more code-level protection it can be robust for practical implementation. Originality/Value: We found several fragmented documents over the web to implement Alexa-enabled virtual devices. After lots of study, we did practical and included the procedure in this research work. From voice input to load trigger, there are lots of steps involved. The complete guidance is not available easily. So through this research work, if someone follows, they can easily create a voice-operated device. This research work may add value to the researcher experimenting with the Alexa command-activated device. Paper Type: Experimental-based Research.

Smart Bag – supported with mobile App

The uses of bags, for travellers, have been an integral part of life. People face difficulties in securing their bags against theft during travel and luggage transit. The emerging Internet of Things technologies and IoT devices like sensors, microcontrollers, GPS/GSM modules, RFID tags/ readers, fingerprint scanner and many such components helps immensely in automation and can be used to collate vast amounts of data, ranging from time- series data from sensors to spatial data. The objective of this project is to make travel bags smart by using the IoT devices and utilizing the captured data to thwart from robbery of personal belongings and to eliminate theft to great extent. The proposed smart bag with a mobile application keeps owner credentials like finger print, passcodes and other security components collected and endorsed using the IoT devices can be used to track the bag. And if the bag is stolen an emergency notifications sent to the owner mobile and used the geographical data to track down to the culprit in precision time before the stolen bag is mutilated. These and other features elaborated in this article helps the law enforcement officers track criminals easily. The smart bag will also benefit banks in secure fund transfer among automatic teller machines and business enterprises in exchanging confidential documents.

Securing Medical Information Transmission Between IoT Devices: An Innovative Hybrid Encryption Scheme Based on Quantum Walk, DNA Encoding, and Chaos

The healthcare industry has undergone a transformation due to the widespread use of advanced communication technologies and wireless sensor networks such as the Internet of Medical Things (IoMT), Health Information Exchange Technology (HIET), Internet of Healthcare Things (IoHT) and Health IoT (HIoT). These technologies have led to an increase in the transmission of medical data, particularly medical imaging data, over various wireless communication channels. However, transmitting high-quality color medical images over insecure internet channels like the Internet and communication networks like 5G presents significant security risks that could threaten patients’ data privacy. Furthermore, this process can also burden the limited bandwidth of the communication channel, leading to delayed data transmission. To address security concerns in healthcare data, researchers have focused a lot of attention on medical image encryption as a means of protecting patient data. This paper presents a color image encryption scheme that integrates multiple encryption techniques, including alternate quantum random walks, controlled Rubik’s Cube transformations, and the integration of the Elliptic Curve Cryptosystem with Hill Cipher (ECCHC). The proposed scheme divides various plaintext images by creating a regular cube by layering planes of a fixed size. Each plane is rotated in an anticlockwise direction, followed by row, column and face swapping, and then DNA encoding is performed. The image cube encoded with DNA is combined with the chaotic cube through DNA addition, and a couple of random DNA sequences are chosen for DNA mutation. After undergoing DNA mutation, the encoded cube is then decoded using DNA. The proposed method has the theoretical capability of encrypting 2D images of unlimited size and number by utilizing an infinitely large cube. The proposed image encryption scheme has been rigorously tested through various experimental simulations and cyberattack analysis, which shows the efficiency and reliability of the proposed encryption scheme.

Automation of structural health monitoring (SHM) system of a bridge using BIMification approach and BIM-based finite element model development

This research focuses on the automation of an existing structural health monitoring system of a bridge using the BIMification approach. This process starts with the Finite Element Analysis (FEA) of an existing bridge for the numerical calculations of static and dynamic parameters. The validation of the FE model and existing SHM system was carried out by the field load testing (Static and dynamic) of the bridge. Further, this study tries to fill the research gap in the area of automatic FE model generation by using a novel methodology that can generate a BIM-based FE model using Visual Programming Language (VPL) scripts. This script can be exported to any FE software to develop the geometry of the FE model. Moreover, the SHM devices are deployed to the Building Information modelling (BIM) model of the bridge to generate the BIM-based sensory model (as per the existing SHM system). In this way, the BIM model is used to manage and monitor the SHM system and control its sensory elements. These sensors are then linked with the self-generated (Internet of Things) IoT platform (coded in Arduino), developing a smart SHM system of the bridge. Resultantly, the system features visualisation and remote accessibility to bridge health monitoring data.

Crop Health Monitoring Using Rasberry Pi and IOT Things

Our main objective is using the IoT sensors provide the real-time status of environmental parameters impacting the crop, and using Raspberry Pi provide the multispectral data used for generating Vegetation Indices (Vis) such as Normalized Difference Vegetation Index (NDVI) to monitor the crop health and environment.

Analysis of the Technology Acceptance Model TAM in understanding Faculty’s behavioral intention to use Internet of Things IOT

The study focuses on examining faculty members’ self-efficacy in two departments – Instructional Technology and Computer Science – in using the Internet of Things (IoT) in Saudi universities. To achieve the study’s goal, the Technology Acceptance Model (TAM) was used to test the effect of self-efficacy in the use of the IoT in education. TAM includes the following variables: Faculty Members’ Self-efficacy (FMSE), Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Attitude (AT), and Behavioral Intention to Use IoT (BI). The study consists of quantitative research, and the instrument used was a survey developed to measure faculty members’ self-efficacy. The results showed that faculty members who have more confidence in their technology skills are more likely to view IoT technology as beneficial. Perceived ease of use affected both perceived usefulness and attitude toward adopting the IoT. However, perceived usefulness failed to affect attitude, and attitude does not influence behavioral intention to adopt IoT technology.

Infusing k-means for securing IoT services in edge computing

Accurate, timely, and safe administration of data from IoT devices is made possible by intelligent computing. As the number of IoT devices proliferates, more and more data will be collected, adding depth and breadth to the existing range of IoT services. Technology that incorporates entire systems on a single integrated circuit has improved to the point where more and more consumer electronics can support full-fledged operating systems. It is impractical to use a single computing model for the entire planet since doing so would cause severe network congestion and security holes. In order to solve this problem, we present a framework that utilizes both blockchain technology and edge computing to provide a lightweight data aggregation and secure data investigation solution for Internet of Things IoT) applications without compromising data security or protection. We use a lightweight data aggregation process at the hub level to keep traffic flowing smoothly and quickly. In order to protect the safety of sensitive data and ensure the precision of IoT AI models, we also offer a multi-level fuzzy hashing process. Preliminary testing demonstrates the viability of the method presented here.

Smart-Grid Monitoring using IoT with Modified Lagranges Key Based Data Transmission

One of the recent advancements in the electrical power systems is the smart-grid technology. For the effective functioning of the smart grid, the process like monitoring and controlling have to be given importance. In this paper, the Wireless Sensor Network (WSN) is utilized for tracking the power in smart grid applications. The smart grid is used to produce the electricity and it is connected with the sensor to transmit or receive the data. The data is transmitted quickly by using the Probabilistic Neural Network (PNN), which aids in identifying the shortest path of the nodes. While transmitting the data from the smart grid to the (Internet of Things) IoT web page, it is secured by introducing the secret keys between the neighbouring nodes through the process of key-management. In this method, the combination of Lagrange’s theorem and the Location Based Key (LBK) management is used for better security performance. This approach delivers optimal performance in terms of security, throughput, packet loss and delay, which are comparatively better than the existing methods.

Web-based Bus Tracking System in the Internet of Things IoT

Public transportation has become integral to daily life, as individuals rely on it to commute between their homes, workplaces, and colleges. However, unnecessary waiting times during transport often result in time wastage. Students frequently find themselves in lines, longing to know the whereabouts of buses and their estimated arrival times at the bus stop. To address these issues, this study presents the development of a web-based system that highlights the routes taken by each bus during its journey. Integrated with Google Maps, the system enables students to conveniently access the routes and schedules of buses. The system provides users with information, including real-time updates on the bus's live location, displayed on the map interface. The system offers additional details about the bus driver, such as their names, phone numbers, bus numbers, and start and end times of their shifts. Users can access this information from anywhere, whether they are at home, work, or college, utilizing the web-based application and an internet connection. Also, a QR code scanning feature is available at bus stops, allowing people to quickly access the desired information. By implementing this system, users, particularly students, gain enhanced visibility into bus routes and schedules, enabling better planning and minimizing waiting times. The web-based platform offers convenience and accessibility, empowering users to make informed decisions about their journeys. The integration of live bus tracking, driver information, and QR code scanning improves the overall user experience and provides a comprehensive solution for public transportation users.

Artificial Intelligence in Smart cities and Healthcare

In the era of the Internet of things IoT and Artificial knowledge (AI) continues to define the century.Artificial intelligence refers to a wide term that incorporates machine learning, normal language handling, rule based expert systems, actual robots, and robotic automation . The rise of computerized system and clinical gadgets in securely and productively diagnosing, treating, and planning care is an obvious sign that AI is digging in for the long haul and fill in significance. While AI holds a great deal of potential, the ramifications for essential consideration suppliers should be tended to as it might restrict execution. Since the Epidemic cities in 2019, the healthcare industry has escalated its AI-based advances by 60%. As indicated by the investigation, AI calculations like ANN, RNN/LSTM, CNN/R-CNN, DNN, and SVM/LS-SVMbhas a higher impact on the different smart city domains. Smart city advances the unification of conventional urban infrastructure and information technology (IT) to improve the quality of living and sustainable urban services in the city. To achieve this, smart cities require coordinated effort among the general public as well as private sectors to introduce IT stages to gather and examine massive amounts of information. Simultaneously, it is vital to design effective artificial intelligence (AI) based tools to deal with medical services emergency circumstances in smart urban communities. This paper reviews about the current technologies like artificial intelligence in the healthcare for smart cities.

How will the internet of energy (IoE) revolutionize the electricity sector? A techno-economic review

As many experts had predicted before, we are experiencing a transitional era from a traditional to a digital society where everything is interconnected with each other. A number of researchers and energy experts including Jeremy Rifkin, the author of the ‘third industrial revolution’ book, have presented a concept that is called the Internet of energy IoE. The concept that is literally the application of the internet of things IoT in the energy sector presents ambitious targets. One of them is to make renewable energy the main global source of energy generation. Several pilot projects have shown that the concept has a great potential to decarbonize, decentralize and digitize our electricity sector. And many countries including China, have adopted action plans to start applying IoE in their electricity sector. We will present in this paper the opportunities that the internet of energy could bring to the electricity sector based on research that was conducted by R&D centers, energy agencies and consulting firms. Our analysis is a systematic review about the potential benefits of IoE applications in the electricity sector. We proposed the different changes that IoE will bring to the three main layers of the electricity sector including the production, distribution/transmission and consumption. We also emphasized on the future architecture of IoE implementation in the power sector taking blockchain as the main electricity trading platform. We conducted a techno-economic case study of the implementation of IoE solutions in real life. Using modeling from Meteonorm, PV-syst and Excel, we analyzed three different scenarios to show the added value of applying IoE solutions to a 6 KWp PV solar farm in Ouarzazat-Morocco. Lastly, we presented key recommendations concerning the development phases of IoE.

Build and Implement Radiation Control using IoT in Parabolic Trough Solar Collector (PTSC)

Connecting the devices to the internet based on the internet of things IoT increases the capability of monitoring and measuring, and controlling essential variables. In this study, the radiation intensity was controlled via the internet of things IoT for PTSC to study the collector's behavior. The light control circuit was designed, built, and implemented. The circuit mainly consists of a power supply, Arduino, relay, and potentiometer. Radiation was successfully monitored using a sensor and displayed through a smartphone via Wi-Fi, and the intensity of radiation light controls the PCM status. A data logging system was applied using a micro SD in a smartphone card and Arduino Node-MCU as a microcontroller. The experimental results show the relationship between solar radiation and resistance change. Inversely, the maximum radiation found from this work was 780 W/m2 with 74 k Ω resistance, and the minimum radiation was 300 W/m2 with 170 k Ω resistance. The output power changes directly through solar radiation, which means the power output with maximum solar radiation will be 3018 W. Using IoT Technology reduces efforts of long-time monitoring during the experiment (many hours).

The convergence of AI, IoT, and big data for advancing flood analytics research

Floods are among the most destructive natural hazards that affect millions of people across the world leading to severe loss of life and damage to properties, critical infrastructure, and the environment. The combination of artificial intelligence (AI), big data, and the Internet of Things (IoTs), has the potential to more accurately predict these extreme events and accelerate the convergence of advanced techniques for flood analytics research. This convergence—so called the Artificial Intelligence of Things (AIoT)—is transformational for both technologies and science-based decision making since AI adds value to IoT through interpretable machine learning (ML) while IoT leverages the power of AI via connectivity and data intelligence. The aim of this research is to discuss the workflow of a Flood Analytics Information System (FAIS; version 4.00) as an example of AIoT prototype to advance and drive the next generation of flood informatics systems. FAIS integrates crowd intelligence, ML, and natural language processing (NLP) to provide flood warning with the aim of improving flood situational awareness and risk assessments. Various image processing algorithms, i.e., Convolutional Neural Networks (CNNs), were also integrated with the FAIS prototype for image label detection, and floodwater level and inundation areas calculation. The prototype successfully identifies a dynamic set of at-risk locations/communities using the USGS river gauge height readings and geotagged tweets intersected with watershed boundary. The list of prioritized locations can be updated, as the river monitoring system and condition change over time (typically every 15 min). The prototype also performs flood frequency analysis (FFA) by fitting multiple probability distributions to the annual flood peak rates and calculates the uncertainty associated with the model. FAIS was operationally tested (beta-tested) during multiple hurricane driven floods in the US and was recently released as a national-scale flood data analytics pipeline.