Internet Of Things Connectivity Research Articles

Impact of Optical-to-Electrical Conversion on the Design of an End-to-End Learning RGB-LED-Based Visible Light Communication System

Visible Light Communication (VLC) is emerging as a promising technology to meet the demands of fifth-generation (5G) networks and the Internet of Things (IoT). This study introduces a novel RGB-LED-based VLC system design that leverages autoencoders, addressing the often overlooked impact of optical-to-electrical (O/E) conversion efficiency. Unlike traditional methods, our autoencoder-based system not only improves communication performance but also mitigates the negative effects of O/E conversion. Through comprehensive simulations, we show that the proposed autoencoder structure enhances system robustness, achieving superior performance compared to traditional VLC systems. By quantitatively assessing the impact of O/E conversion—a critical aspect previously overlooked in the literature—our work bridges a crucial gap in VLC research. This contribution not only advances the understanding of VLC systems but also provides a strong foundation for future enhancements in 5G and IoT connectivity.

Synergy of 6G technology and IoT networks for transformative applications

SummaryThe rapid growth of Wi‐Fi networking and intelligent systems, fueled by the emergence of the Internet of Things (IoT), has enabled significant transformative advancements. The imminent arrival of sixth‐generation (6G) wireless networks offers more opportunities as fifth‐generation (5G) wireless networks improve IoT connections. This study explores the potential advantages of 6G technology and IoT networks, focusing on edge intelligence, reconfigurable smart surfaces, Terahertz communications, and blockchain integration. The study examines potential implementation challenges and highlights the potential impact of 6G on IoT device usage. This research outlines potential applications of 6G in many sectors like the internet of vehicles, healthcare, autonomous driving, unmanned aerial vehicles, satellite television, and industrial IoT. This research elaborates on specific research topics related to 6G‐IoT technologies to enhance understanding and practical applicability.

Design and Evaluation of a Low-Power Wide-Area Network (LPWAN)-Based Emergency Response System for Individuals with Special Needs in Smart Buildings.

The Internet of Things (IoT) is a growing network of interconnected devices used in transportation, finance, public services, healthcare, smart cities, surveillance, and agriculture. IoT devices are increasingly integrated into mobile assets like trains, cars, and airplanes. Among the IoT components, wearable sensors are expected to reach three billion by 2050, becoming more common in smart environments like buildings, campuses, and healthcare facilities. A notable IoT application is the smart campus for educational purposes. Timely notifications are essential in critical scenarios. IoT devices gather and relay important information in real time to individuals with special needs via mobile applications and connected devices, aiding health-monitoring and decision-making. Ensuring IoT connectivity with end users requires long-range communication, low power consumption, and cost-effectiveness. The LPWAN is a promising technology for meeting these needs, offering a low cost, long range, and minimal power use. Despite their potential, mobile IoT and LPWANs in healthcare, especially for emergency response systems, have not received adequate research attention. Our study evaluated an LPWAN-based emergency response system for visually impaired individuals on the Hazara University campus in Mansehra, Pakistan. Experiments showed that the LPWAN technology is reliable, with 98% reliability, and suitable for implementing emergency response systems in smart campus environments.

Unveiling New IoT Antenna Developments: Planar Multibeam Metasurface Half-Maxwell Fish-Eye Lens with Wavelength Etching

This study introduces a groundbreaking antenna system, the directive Metasurface Half-Maxwell Fish-Eye (MHMF) lens antenna, tailored specifically for Internet-of-Things (IoT) networks. Designed to operate at 60 GHz, this antenna ingeniously integrates a dipole antenna within a parallel-plate waveguide to illuminate a Half-Maxwell Fish-Eye (HMFE) lens. The HMFE lens serves as a focal point, enabling a crucial high gain for IoT operations. The integration of metasurface structures facilitates the attainment of the gradient refractive index essential for the lens surface. By employing commercial Ansys HFSS software, extensive numerical simulations were conducted to meticulously refine the design, focusing particularly on optimizing the dimensions of unit cells, notably the modified H-shaped cells within the parallel waveguides housing the beam launchers. A functional prototype of the antenna was constructed using a standard PCB manufacturing process. Rigorous testing in an anechoic chamber confirmed the functionality of these manufactured devices, with the experimental results closely aligning with the simulated findings. Far-field measurements have further confirmed the effectiveness of the antenna, establishing it as a high-gain antenna solution suitable for IoT applications. Specifically, it operates effectively within the 60 GHz range of the electromagnetic spectrum, which is crucial for ensuring reliable communication in IoT devices. The directive HMFE lens antenna represents a significant advancement in enhancing IoT connectivity and capabilities. Leveraging innovative design concepts and metasurface technology, it heralds a new era of adaptable and efficient IoT systems.

IoT Enabled Real Time Low Cost Cardiac Monitor Using LabVIEW

The rapid advancement of the Internet of Things (IoT) and medical technology has paved the way for innovative healthcare solutions. The system incorporates IoT connectivity to enable remote monitoring, data collection, and analysis, enhancing patient care and medical decision making. Cardiac monitoring system used in hospitals to measure and record the cardiac parameters. Vital parameters are transferred within the hospitals either using Wi-Fi or Bluetooth. Range of transmission for such wireless communication is only effective within the hospitals and further transfer to a long distance is limited. The proposed cardiac monitoring system is developed using LabVIEW environment - a versatile Graphical User Interface (GUI). Data acquired through the electrodes are connected to my DAQ Unit (Data Acquisition Unit) which helps to integrate electrodes with computer or PC. Data acquired from the Software is connected to the firebase console and it will help the practitioners to share the data in live and updated. It offers benefits such as early detection of cardiac irregularities such as arrythmia, reduced hospitalization periods, and improved patient outcomes. Additionally, healthcare practitioners and caretakers can remotely access patient data, enabling timely interventions and personalized treatment plans. Since the cardiac monitors are often used by bedside patients, it may introduce bed sores in them. Hence, in addition to these parameters, body moisture level and temperature of the patient are measured using DHT11(temperature and humidity sensor) to ensure the prevention of bedsores. These additional parameters measured are also enabled to view through IoT.

Enhanced EV Battery Monitoring Using IoT with Improved SEPIC - ZETA Converter and Modified Lion Optimization for Photovoltaic Systems

The rising popularity of electric vehicles (EVs) and the increasing emphasis on sustainable transportation have highlighted the importance of advanced monitoring systems. These systems play a crucial role in providing real-time information about battery parameters to ensure optimal performance and longevity. Moreover, the integration of renewable energy sources, specifically photovoltaic (PV) systems, with EV charging infrastructure presents an exciting prospect to enhance energy efficiency and minimize environmental harm. As a consequence the proposed work develops an Internet of Things (IoT) based PV fed EV charging system. The system incorporates an improved SEPIC-Zeta converter together with Modified Lion Optimization algorithm (LOA) assisted Proportional Integral (PI) controller for optimizing PV system for charging EV battery. IoT connectivity monitors parameter such as PV voltage, PV current, and State of Charge (SOC) of battery. Real-time monitoring of these parameters is achieved by leveraging sensors. The collected data is transmitted through IoT networks to a central monitoring system, enabling operators to track the performance of PV system and EV battery. This facilitates optimized energy generation, efficient battery charging and discharging, and overall system reliability. IoT-enabled monitoring system provides remote accessibility, data analytics, and the generation of alerts and notifications for timely actions. Experimental validation demonstrates that, the proposed concept enhances the monitoring capabilities, improves energy efficiency, and ensures reliable operation of EV charging infrastructure.

IoT- Based Drowsiness Monitoring and Crash Detection System to Enhance Road Safety

This project is a solution designed to address the critical issue of driver drowsiness and enhance road safety. The system leverages the power of the Internet of Things (IoT) to continuously monitor driver alertness and promptly detect potential accidents. It comprises a network of sensors strategically placed within the vehicle, including facial recognition cameras and accelerometers. These sensors work together to capture and analyze a driver's physiological and behavioural data in real-time. Facial recognition technology detects signs of drowsiness such as drooping eyelids and yawning. Through a secure IoT connection, this data is transmitted to a central processing unit within the vehicle. Advanced algorithms process this information, assessing the driver's state of alertness. In the event of detected drowsiness, the system initiates a series of proactive interventions, such as sounding alarms, vibrating the driver's seat, or even communicating with an external monitoring centre for further assistance. Moreover, the system's crash detection capabilities are enabled by the accelerometers, which monitor sudden changes in the vehicle's motion. If a collision or accident is detected, the system promptly sends an alert, including the vehicle's GPS coordinates, to emergency services or designated contacts, facilitating rapid response and potentially saving lives. Keywords:- Drowsiness, Crash Detection, Raspberry Pi, IoT

IoT-driven accessibility: A refreshable OCR-Braille solution for visually impaired and deaf-blind users through WSN

The spectacular concept of integrating OCR with the Internet of Things (IoT) and Wireless Sensor Networks (WSN), presented in this study, intends to increase the autonomy and social inclusion of people with visual impairments and deaf-blindness. This application converts text from photographs into real-time Braille representations by utilizing the capabilities of Optical Character Recognition (OCR) technology, Braille displays, and IoT. Braille is a tactile form of writing which assists the visually impaired by representing letters and numbers with raised dots. Text recognition and conversion through OCR helps people with vision issues by converting printed text into accessible formats like audio or Braille, assisting people in with recognizing things around them. Individuals with visual impairments are given autonomous access to critical information by smoothly integrating modern technologies, boosting their self-confidence and promoting active social involvement. This OCR-Braille approach's primary objective is to minimize the knowledge gap and promote social equality. Users' ease of access to labels, educational resources, and digital information about their environment fosters a sense of empowerment and independence. This ground-breaking study not only eliminates the accessibility gap but also provides the groundwork for a society that is better linked and accessible. Individuals have access to the tools they need for independently navigating their surroundings through simple IoT connectivity and WSN. This research lays the path for a future for assistive technology to catalyze equality and independence, independent of one's visual ability, by fusing assistive technology and IoT connectivity.

Impact of Internet of Things on Home Appliances

The way household appliances operate and communicate with consumers has completely changed as a result of the Internet of Things (IoT). This abstract explores how the Internet of Things affects household appliances, emphasizing how it affects user experience, convenience, and energy efficiency. With the use of smartphones and other smart devices and IoT connectivity, users can effortlessly integrate and control their appliances, giving them the ability to monitor and operate them remotely from any location. Tasks like receiving notifications, changing settings, and even starting appliance functions when away from home are made possible by this convenience. Furthermore, by using automation and data-driven insights, IoT makes it possible for home appliances to operate more energy efficiently. With sensors and connectivity, smart appliances can adjust their performance according to usage patterns and environmental factors in real time, saving energy and money on utility bills. IoT-enabled appliances can also take part in demand response initiatives, which helps with overall energy saving efforts. IoT-enabled appliances greatly improve user experience with their customizable features and user-friendly interfaces. The performance and lifespan of appliances are increased by machine learning algorithms that examine user behavior and preferences to make personalized suggestions, optimize settings, and foresee maintenance requirements. Keywords: Communication, Smart devices, Connectivity, Remotely, Sensors, Automation, Customizable features, User- friendly, Energy efficiently

Enhancing Throughput in IoT Networks: The Impact of Active RIS on Wireless Powered Communication Systems

This paper investigates the potential of active reconfigurable intelligent surfaces (RIS) to enhance wireless-powered communication networks (WPCNs), addressing the evolving connectivity needs of the internet of things (IoT). Active RIS, capable of amplifying and reflecting signals, offers a solution to surpass the limitations of passive RIS, such as double-fading attenuation, aiming to significantly improve network throughput and coverage. Our research focuses on exploiting the amplification capabilities of active RIS to boost the overall network sum throughput, engaging in a comprehensive optimization of critical network parameters, including time allocation, reflection coefficients, and phase shift matrices specific to active RIS. The formulated problem is non-convex and highly complex due to the coupling of optimization variables. We employed a successive convex approximation algorithm to solve the throughput maximization problem by converting the non-convex constraints into approximated convex constraints and solving them iteratively. Through extensive simulations, we demonstrate that our active RIS-assisted network substantially outperforms networks facilitated by passive RIS, marking a significant advancement in WPCN performance. These findings underscore the potential of active RIS technology in realizing the full capabilities of IoT connectivity.

Smart Hydroponic Systems: Optimizing Nutrient Levels with IoT Connectivity

Maintaining precise nutrient levels is essential for the thriving success of hydroponic systems. This comprehensive study delves into the intricate interplay of climatic conditions and nutrients, meticulously analysing various parameters like Total Dissolved Solids (TDS), pH, and electrical conductivity (EC) within a sophisticated smart hydroponic vertical Nutrient Film Technique (NFT) setup designed for leafy greens. The innovative system integrates a wireless sensor network and Internet of Things (IoT) connectivity, employing ESP32 microcontrollers as the primary unit alongside complementary hardware components for continuous and real-time monitoring of critical nutrient parameters. The investigation delves into the dynamic relationship between environmental factors and the growth patterns of spinach plants. Through a thorough examination of the extensive dataset gathered via deployed sensors, the study unveils variations in environmental parameters throughout various stages of plant development, including germination and root establishment. The study aims to elucidate the significance of each parameter in optimizing plant growth in hydroponic environments by analysing data associations. Results show higher Total Dissolved Solids (TDS) values correlate with better plant growth, while reduced pH levels harm plants. These findings are crucial for interpreting disease symptoms, aiding farmers in identifying issues early and optimizing yields. Understanding how nutrient values affect plant health enables proactive problem-solving. This research provides valuable insights into smart hydroponic systems, informing precision agriculture decisions.

Smart Hydroponic Systems: Optimizing Nutrient Levels with IoT Connectivity

Maintaining precise nutrient levels is essential for the thriving success of hydroponic systems. This comprehensive study delves into the intricate interplay of climatic conditions and nutrients, meticulously analysing various parameters like Total Dissolved Solids (TDS), pH, and electrical conductivity (EC) within a sophisticated smart hydroponic vertical Nutrient Film Technique (NFT) setup designed for leafy greens. The innovative system integrates a wireless sensor network and Internet of Things (IoT) connectivity, employing ESP32 microcontrollers as the primary unit alongside complementary hardware components for continuous and real-time monitoring of critical nutrient parameters. The investigation delves into the dynamic relationship between environmental factors and the growth patterns of spinach plants. Through a thorough examination of the extensive dataset gathered via deployed sensors, the study unveils variations in environmental parameters throughout various stages of plant development, including germination and root establishment. The study aims to elucidate the significance of each parameter in optimizing plant growth in hydroponic environments by analysing data associations. Results show higher Total Dissolved Solids (TDS) values correlate with better plant growth, while reduced pH levels harm plants. These findings are crucial for interpreting disease symptoms, aiding farmers in identifying issues early and optimizing yields. Understanding how nutrient values affect plant health enables proactive problem-solving. This research provides valuable insights into smart hydroponic systems, informing precision agriculture decisions.

Solar based Smart Sanitizer Dispenser System with Internet of Things (IoT) Technology

In response to the growing demand for efficient and sustainable hygiene solutions, this project introduces a Solar-Powered Smart Sanitizer Dispenser System leveraging IoT technology. The system aims to address the need for touchless and accessible hand sanitization in various environments, including public spaces, healthcare facilities, and commercial establishments. By integrating solar power as the primary energy source, the system offers autonomy and eco-friendliness, reducing dependency on conventional electricity grids and minimizing environmental impact. The core components of the system include a smart dispenser unit equipped with sensors for detecting hand proximity, a reservoir for storing sanitizer solution, and a microcontroller unit responsible for data processing and IoT connectivity. Through the IoT interface, users can remotely monitor sanitizer levels, receive real-time usage statistics, and manage dispenser settings, enhancing operational efficiency and maintenance. Furthermore, the incorporation of solar panels ensures continuous operation even in off-grid locations, making the system suitable for deployment in remote or outdoor settings where access to electricity may be limited. Maximizing the efficacy of solar power conversion and extending operational uptime.

Exploring Universal Filtered Multi Carrier Waveform for Last Meter Connectivity in 6G: A Street-Lighting-Driven Approach with Enhanced Simulator for IoT Application Dimensioning

In the dynamic landscape of 6G and smart cities, visible light communication (VLC) assumes critical significance for Internet of Things (IoT) applications spanning diverse sectors. The escalating demand for bandwidth and data underscores the need for innovative solutions, positioning VLC as a complementary technology within the electromagnetic spectrum. This paper focuses on the relevance of VLC in the 6G paradigm, shedding light on its applicability across smart cities and industries. The paper highlights the growing efficiency of lighting LEDs in infrastructure, facilitating the seamless integration of VLC. The study then emphasizes VLC’s robustness in outdoor settings, demonstrating effective communication up to 10 m. This resilience positions VLC as a key player in addressing the very last meter of wireless communication, offering a seamless solution for IoT connectivity. By introducing a freely available open-source simulator combined with an alternative waveform, UFMC, the study empowers researchers to dimension applications effectively, showcasing VLC’s potential to improve wireless communication in the evolving landscape of 6G and smart cities.

AN ANALYSIS OF THE HETEROGENEOUS IOT DEVICE NETWORK INTERACTION IN A CYBER-PHYSICAL SYSTEM

The article is devoted to the study of existing technologies regarding Internet of Things (IoT) device interaction in a heterogeneous network. Since each smart home appliance can be controlled by a customer who aims to find a cost-effective and easy-to-connect product for their own connected home, there are certain functional limitations for devices from distinct manufacturers that may decrease the intention to merge them all into a single network. A variety of proprietary protocols and communication standards embedded by vendors make their products unable to interact with other vendor devices if the connection standard used is not identical. Also, an IoT product design refers to its own functionality, mainly excluding the possibility of integration into other existing infrastructure. As IoT equipment emerges on the market, the complexity of its connection to a heterogeneous network corresponds to the firmware and the standard unification according to modern demands. It means that potential users might face the necessity of overcoming these issues to achieve high performance in terms of network interoperability. In general, an IoT gateway operating as a middleware might have the potential to enable a network with distinct communication models to operate without failure or data loss. This task requires the received data to be converted into the format in which the data is intended. This paper includes a comparative analysis of existing IoT device interaction standards, connection protocols, and data transfer technologies, evaluating their features for an effective adoption of the proposed network architecture, which can be used to improve the interoperability of heterogeneous IoT devices.

Proactive defense mechanism: Enhancing IoT security through diversity-based moving target defense and cyber deception

The Internet of Things (IoT) has become increasingly prevalent in various aspects of our lives, enabling billions of devices to connect and communicate seamlessly. However, the intricate nature of IoT connections and device vulnerabilities exposes the devices to security threats. To address the security challenges, we propose a proactive defense framework that leverages a model-based approach for security analysis and facilitates the defense strategies. Our proposed approach incorporates proactive defense mechanisms that combine Moving Target Defense techniques with cyber deception. The proposed approach involves the use of a decoy nodes as a deception technique and operating system based diversity as a moving target defense strategy to change the attack surface area of IoT networks. Additionally, we introduce a technique known as Important Measure-based Operating System Diversity to reduce defense cost. The effectiveness of the defense mechanisms was evaluated by using a graphical security model in a Software Defined Networking-based IoT network. Simulation results demonstrate the effectiveness of our approach in mitigating the impact of attacks while maintaining high performance levels in IoT networks.

Penguin search with Harris-Hawk optimization algorithm to improve clustering performance in wireless network

<span>Integrating optimal search algorithm concepts across the wireless core and cluster structure enables next-generation wireless networks to effectively provide reliable low-delay communications and connectivity for internet of things (IoT) devices. This article describes penguin search with the Harris-Hawk optimization algorithm (PHHO) to improve clustering performance in wireless networks. The penguin search optimization algorithm (PSO) algorithm computes the fitness value for feature selection from the database. Harris-Hawk optimization (HHO) algorithm to reduce the time and energy required for network transmission. This mechanism builds the clusters based on node communication range. The node direction, node mobility, node bandwidth availability, and energy parameters to decide the cluster head (CH) by applying the HHO algorithm. This approach uses a PSO algorithm fitness function to select the feature subset to minimize error and overhead in the network. Using a network simulator (NS)-3, this method assesses and chooses the most efficient way for data transmission, and the result is compared to a baseline mechanism.</span>

Multiple Access Design for Symbiotic Radios: Facilitating Massive IoT Connections With Cellular Networks

Symbiotic radio (SR) has emerged as a spectrum-and energy-efficient paradigm to support massive Internet of Things (IoT) connections. Two multiple access schemes are proposed in this paper to facilitate massive IoT connections using the cellular network based on the SR technique, namely, the simultaneous access (SA) scheme and the selection diversity access (SDA) scheme. In the SA scheme, the base station (BS) transmits information to the receiver while multiple IoT devices transmit their information simultaneously by passively backscattering the BS signal to the receiver, while in the SDA scheme, only the IoT device with the strongest backscatter link transmits information. In both of the schemes, the receiver jointly decodes the information from the BS and IoT devices. To evaluate the above two schemes, the closed-form expressions of the ergodic rates in high signal-to-noise ratio (SNR) regimes and outage probabilities for cellular and IoT transmissions are derived by using extreme value theory, generalized-K distribution approximation and Gaussian-Chebyshev quadrature methods. Finally, numerical results are provided to verify the theoretical analysis and compare the proposed multiple access schemes. When the number of IoT devices is small, the SDA scheme is more appealing since it can significantly reduce the computational complexity while achieving equivalent performance to the SA scheme. When the number of IoT devices is large, the SA scheme is preferable since it guarantees a significantly better rate performance and a lower outage probability.

Optimized LoRaWAN Architectures: Enhancing Energy Efficiency and Long-Range Connectivity in IoT Networks for Sustainable, Low-Power Solutions and Future Integrations with Edge Computing and 5G

The Internet of Things (IoT) has expanded rapidly, allowing for a network of sensors and gadgets to collect and share information to make people's lives easier and more convenient. As the Internet of Things (IoT) grows, however, energy efficiency becomes a major issue, especially for portable and wireless gadgets. Low-power, long-range communication capabilities are needed, and Long-Range Wide Area Network (LoRaWAN) has emerged as a viable solution to meet this need. This study provides an in-depth analysis of the LoRaWAN-based, low-power Internet of Things. The suggested network architecture is optimized for low power consumption and high connectivity for numerous Internet of Things (IoT) use cases. This low-power Internet of Things network relies on LoRaWAN gateways, end devices, and a server to function. LoRaWAN is a technology that enables the low-power, long-range transmission of data packets. The results show that the optimized case and non-optimized case have a delivery ratio of 0.85 to 0.73 from node 100 to 500. LoRaWAN significantly reduces energy usage compared to conventional IoT connectivity alternatives, making it a fantastic option for battery-powered devices in far-flung or limited-resource locations. Finally, the adoption of LoRaWAN provides a viable solution to address the energy efficiency concerns in IoT networks, hence allowing for sustainable, long-lasting IoT installations and enabling a wide variety of new applications within the IoT ecosystem. Furthermore, addresses the potential applications of this technology in the future, including upgrades and integration with other technologies like edge computing and 5G networks.

Pengembangan Media Pembelajaran Matematika Berbasis IoT dengan Pendekatan Problem Based Learning

This research aims to develop an Internet of Things (IoT)-based mathematics learning medium using a Problem-Based Learning (PBL) approach and evaluate its effectiveness in enhancing students' problem-solving skills. The research method employed is Research and Development (R&D), consisting of stages such as needs analysis, media design, prototype development, field trial, and evaluation. The research subjects consist of 11th-grade students at MAN 1 Probolinggo. The IoT-based mathematics learning medium is designed to facilitate dynamic interaction between students and real-world objects through IoT connectivity. This medium allows students to experience direct learning and actively participate in solving mathematical problems in real-life contexts. The results of this research anticipate that the use of IoT-based learning media with a PBL approach significantly improves problem-solving skills compared to conventional learning methods. Furthermore, it is expected that positive responses from students and teachers to this medium can be integrated into existing mathematics curricula. Therefore, the development of IoT-based mathematics learning media with a PBL approach is expected to be an effective alternative in enhancing students' mathematical problem-solving skills. This medium enables students to actively engage in learning, fosters creativity, and connects mathematical concepts with the real world. Additionally, the results of this research are expected to make a positive contribution to the development of innovative and technology-relevant mathematics teaching methods.