Internet Of Things Capabilities Research Articles

IOT Based Food Minitoring System

Abstract: The Internet of Things (IoT) has emerged as a transformative technology with wide-ranging applications, and one of its promising domains is in the field of food monitoring systems. This abstract introduces an innovative IoT-based Food Monitoring System designed to enhance food quality assurance and reduce waste in the supply chain. The proposed system integrates various IoT components, including sensors, actuators, and communication devices, to create a comprehensive solution for monitoring the entire lifecycle of food products. Key objectives of the system include real-time tracking of food conditions, ensuring compliance with quality standards, and minimizing the environmental impact associated with food waste. The implementation of this IoT-based Food Monitoring System offers several benefits, including improved food quality, reduced waste, increased operational efficiency, and enhanced consumer satisfaction. By leveraging the capabilities of IoT, this system addresses the challenges associated with maintaining food quality and safety while contributing to the overall sustainability of the food industry

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.

Green thinking: impact of smart technologies on supply chain management

Green thinking: impact of smart technologies on supply chain management

IOT Based Anti - Theft Flooring System Using NodeMCU (ESP8266)

Traditional anti-theft security systems often rely on easily circumvented methods such as motion sensors or wall-mounted devices, leaving vulnerabilities that can be exploited by savvy thieves. To address these limitations, we propose an innovative IoT-based anti-theft flooring system utilizing Node MCU technology. This system offers comprehensive monitoring of designated areas, detecting any movement within its coverage zone. Each secure flooring tile within the system is seamlessly integrated with IoT capabilities. Upon activation, the system begins monitoring the area, transmitting data over the internet to alert users of any intrusions. When an unauthorized individual steps onto the floor, sensors promptly detect the movement and relay the information to the central controller. The controller verifies the signal's validity and triggers the camera to capture images of the detected movement area. These images are then transmitted over the internet, allowing the owner to remotely assess the situation in real-time. By leveraging IoT technology, our anti-theft flooring system offers enhanced security measures, providing peace of mind for property owners. Keywords: IoT (Internet of Things), Anti-theft system, Flooring security, NodeMCU (ESP8266) ,IoT security , Real time monitoring.

Wireless Sensor Networks Empowered by IOT for Air Quality Monitoring

This is a thorough method of monitoring air quality by integrating the Internet of Things (IoT) with Wireless Sensor Networks (WSNs). This approach seeks to improve air quality evaluations' accuracy and efficiency by utilizing the interconnectedness of IoT devices. The integration of WSNs, Internet of Things capabilities, and sophisticated filtering methods in this project helps to build reliable systems for monitoring air quality in real-time, which is essential for managing public health and environmental sustainability.

Towards circular economy: A IoT enabled framework for circular supply chain integration

Nowadays, the Internet of Things (IoT) has evolved beyond mere buzzword status, emerging as a pivotal force that can confer a competitive advantage in the market. By facilitating seamless communication between objects and the internet, IoT catalyzes unprecedented connectivity between machines and objects. An inherent advantage lies in its capacity to facilitate real-time information sharing, enabling efficient management of vital aspects within the realm of supply chain management, including inventory, products, and orders. Therefore, this study investigates the impact of IoT on supply chain performance, with a specific focus on the mediating role of interconnected systems in the dynamics of supply and demand, and the performance of supply chain firms within a sustainable circular economy context. A survey involving 268 manufacturers forms the basis of quantitative data analysis. Partial Least Square Structural Equation Modelling (PLS-SEM) was employed to test the relationships between latent and construct factors. The results highlight the significant influence of IoT capabilities on both supply chain performance and the integration of internet-enabled supply and demand processes. Concurrently, the study reveals a reciprocal positive effect, as supply and demand integration within internet-enabled supply chains contributes to enhanced supply chain performance. Moreover, the integration of internet-enabled supply and demand processes emerges as a crucial mediator, amplifying the relationship between IoT capabilities and supply chain performance. This study provides valuable insights for managers, researchers, and policymakers, fostering a deeper understanding of the vital role that IoT plays in cultivating and enhancing superior supply chain management practices and overall performance. The study highlights the significant benefits of IoT in enhancing supply chain performance through improved real-time tracking, inventory management, and resource optimization. It also emphasizes the crucial role of integrating internet-enabled supply and demand processes as a mediator, boosting overall supply chain efficiency and responsiveness.

Valuation of Internet of Energy (IoE) Platforms in Smart Cities: A Hybrid Multi-Criteria Decision Making Approach

A smart city is a place where people live using computing, sensing, and networking technology in a variety of ways, including smart buildings, smart homes, smart transportation, smart workplaces, smart offices, smart industries, and smart agriculture. These smart technologies need to connect so; we need to use the Internet of Things (IoT) that has applications in many areas of our smart lives. IoT has been used due to the growing usage of renewable energy sources and the challenges of network management. Internet of Energy (IoE) integrates the IoT and smart grid capabilities. The basic role of smart grids or IoE is an essential element in creating smart cities. In this work, we present some IoE platforms that represent the alternatives and their criteria. The proposed study treats the uncertainty of multi-criteria decision-making (MCDM) modified by single value triangular neutrosophic number (SVTrN) by choosing the optimal IoE platform based on the criteria importance through inter-criteria correlation (CRITIC) method and multi-attributive ideal-real comparative analysis (MAIRCA). The proposed model proved its effectiveness by applying it to an experimental case. The results show that the DCC (A3) platform is the best one.

Revolutionizing Retail: Examining the Influence of Blockchain-Enabled IoT Capabilities on Sustainable Firm Performance

Blockchain has revolutionized the field of supply chain management, allowing firms to optimize their operations and achieve enhanced levels of efficiency and environmental responsibility. This study investigates the relationships between the functionalities of the blockchain-enabled Internet of Things (IoT) and many aspects of the supply chain, namely, supplier integration, internal integration, customer integration, and sustainable logistic capabilities. It also analyses the impact of these correlations on the supply chain performance and sustainability of firms. This study is grounded in an empirical inquiry carried out using a questionnaire survey of the retail industry in Pakistan. Partial Least Squares Structural Equation Modelling (PLS-SEM) was employed to analyze the data. The findings indicate a direct correlation between the use of BC-enabled Internet of Things (IoT) capabilities and the integration of the supply chain, as well as logistic capabilities. Furthermore, there is a strong and meaningful correlation between blockchain-enabled supply chain integration and sustainable logistic capabilities and firm performance. The research findings indicate that the combined impact of digital innovations results in higher levels of corporate performance and sustainability. By embracing digitization through blockchain technology, business organizations can attain supply chain excellence. This integration enhances the adoption of environmentally beneficial actions, minimizes waste, and decreases carbon emissions across supply chains, thus reinforcing the connection between sustainable firm performance and environmental sustainability. As a result, the enterprises may execute sustainably through improved logistical capabilities and effective integration. The results hold great theoretical and practical significance for improving supply chain management efficacy and accomplishing multiple SDGs, including SDG-8, SDG-9, SDG-11, and SDG-12.

IoT Enabled 3D Printer Device for Bio models

IoT and embedded electronics is getting popular due to its versatile applications in various fields for domestic, commercial and industrial usage. However electronics or electrical systems that are primarily built using electronics, needs enclosures to protect it from the environment as well as for maintaining its privacy concerns. 3D printers are valuable to rapidly prototype/fabricate/build enclosures for custom applications. The steps, involved in rapid prototyping using 3D printers start from understanding the specification and measurement requirements e.g. colour, look, dimensions, and tolerances. Cura is a popular slicing software used in 3D printing that converts your 3D models (STL files) into a format (G-code) that your 3D printer can understand. Integrating IoT (Internet of Things) with 3D printing using Modified OctoPrint. It can greatly enhance the functionality and accessibility of your 3D printing setup. OctoPrint is an open-source software that allows you to control and monitor your 3D printer remotely via a web interface. By adding IoT capabilities, you can further automate and monitor your printing processes, making them more efficient and comfort.

Real-Time Monitoring 3D Printer Device for Bio Models

IoT and embedded electronics is getting popular due to its versatile applications in various fields for domestic, commercial and industrial usage. However electronics or electrical systems that are primarily built using electronics, needs enclosures to protect it from the environment as well as for maintaining its privacy concerns. 3D printers are valuable to rapidly prototype/fabricate/build enclosures for custom applications. The steps, involved in rapid prototyping using 3D printers start from understanding the specification and measurement requirements e.g. colour, look, dimensions, and tolerances. Followed by Certainly! Cura is a popular slicing software used in 3D printing that converts your 3D models (STL files) into a format (G-code) that your 3D printer can understand. Integrating IoT (Internet of Things) with 3D printing using Modified OctoPrint. It can greatly enhance the functionality and accessibility of your 3D printing setup. OctoPrint is an open-source software that allows you to control and monitor your 3D printer remotely via a web interface. By adding IoT capabilities, you can further automate and monitor your printing processes, making them more efficient and comfort

Ekalusugan: An Intelligent health observation system using Internet of Things

- In today's technological landscape, the Internet of Things (IoT) has ushered in a multitude of applications, with wearable technology and smart healthcare standing out as paramount. Amidst this backdrop, we present "eKalusugan," an innovative intelligent health monitoring system harnessed by IoT. Traditional health observation systems often fall short in catering to the needs of sick patients, a concern this study addresses through an insightful exploration of challenges and innovative remedies. Our work also delves into the evaluation of a prototype observation system, gauging user acceptance based on its novel features. Employing a mixed-methods approach, encompassing both a comprehensive questionnaire and in-depth interviews, we engaged five (5) medical experts, thirty (30) healthcare providers, and eighty (80) patients from diverse locales. This collaborative effort yielded invaluable insights into the existing gaps, such as inadequate sickness monitoring, role ambiguity, and the struggle to maintain comprehensive medical histories under the conventional model. To surmount these limitations, our proposed solution boasts two pivotal facets. First, we advocate for leveraging IoT's capabilities to streamline the creation of an intelligent health observation system. Second, we emphasize the necessity of a user-centric approach, rendering the system significantly more intuitive for medical professionals and patients alike, in stark contrast to conventional methods. Our findings underscore the potency of the eKalusugan system, with respondents lauding its functionality (rated 4.62), reliability (rated 4.52), usability (rated 4.68), and performance (rated 4.70) as either excellent or good (with an average rating of 4.59). Encouragingly, our study indicates that the envisaged system could potentially gain traction at the behest of governmental health agencies, paving the way for its integration in monitoring the well-being of sick individuals. In this era where the confluence of IoT and healthcare beckons transformative progress, eKalusugan shines as a testament to the possibilities that emerge when cutting-edge technology aligns with human well-being

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.

Enhancing Meditation Techniques and Insights Using Feature Analysis of Electroencephalography (EEG)

Through a Bluetooth connection between the Muse 2 device and the meditation app, leveraging IoT capabilities. The methodology encompasses data collection, preprocessing, feature extraction, and model training, all while utilizing Internet of Things (IoT) functionalities. The Muse 2 device records EEG data from multiple electrodes, which is then processed and analyzed within a mobile meditation platform. Preprocessing steps involve eliminating redundant columns, handling missing data, normalizing, and filtering, making use of IoT-enabled techniques. Feature extraction is carried out on EEG signals, utilizing statistical measures such as mean, standard deviation, and entropy. Three different models, including Support Vector Machine (SVM), Random Forest, and Multi-Layer Perceptron (MLP), are trained using the preprocessed data, incorporating Internet of Things (IoT) based methodologies. Model performance is assessed using metrics like accuracy, precision, recall, and F1-score, highlighting the effectiveness of IoT-driven techniques. Notably, the MLP and Random Forest models demonstrate remarkable accuracy and precision, underlining the potential of this IoT-integrated approach. Specifically, the three models achieved high accuracies, with Random Forest leading at 0.999, followed by SVM at 0.959 and MLP at 0.99. This study not only contributes to the field of brain-computer interfaces and assistive technologies but also showcases a viable method to seamlessly integrate the Muse 2 device into meditation practices, promoting self-awareness and mindfulness with the added power of IoT technology.

Innovative IoT-based intelligent smart cup coaster for enhanced beverage experience

The Innovative IoT-Based Intelligent Smart Cup Coaster presented in this research introduces a transformative approach to the traditional beverage coaster by seamlessly integrating cutting-edge Internet of Things (IoT) technology. This intelligent coaster is designed to enhance the overall beverage experience, addressing the limitations of conventional coasters. Equipped with temperature, weight, and proximity sensors, the smart cup coaster communicates wirelessly with a dedicated mobile application, allowing users to personalize and control various aspects of their beverage enjoyment. Features such as real-time temperature control, weight sensing, proximity awareness, customizable LED lighting, and integration with virtual assistants redefine the user experience. By leveraging IoT capabilities, this smart coaster not only elevates the functionality of a commonplace object but also offers valuable insights into consumption patterns, encouraging hydration and providing a dynamic and interactive beverage experience for modern consumers.

A Novel IDS with a Dynamic Access Control Algorithm to Detect and Defend Intrusion at IoT Nodes.

The Internet of Things (IoT) is the underlying technology that has enabled connecting daily apparatus to the Internet and enjoying the facilities of smart services. IoT marketing is experiencing an impressive 16.7% growth rate and is a nearly USD 300.3 billion market. These eye-catching figures have made it an attractive playground for cybercriminals. IoT devices are built using resource-constrained architecture to offer compact sizes and competitive prices. As a result, integrating sophisticated cybersecurity features is beyond the scope of the computational capabilities of IoT. All of these have contributed to a surge in IoT intrusion. This paper presents an LSTM-based Intrusion Detection System (IDS) with a Dynamic Access Control (DAC) algorithm that not only detects but also defends against intrusion. This novel approach has achieved an impressive 97.16% validation accuracy. Unlike most of the IDSs, the model of the proposed IDS has been selected and optimized through mathematical analysis. Additionally, it boasts the ability to identify a wider range of threats (14 to be exact) compared to other IDS solutions, translating to enhanced security. Furthermore, it has been fine-tuned to strike a balance between accurately flagging threats and minimizing false alarms. Its impressive performance metrics (precision, recall, and F1 score all hovering around 97%) showcase the potential of this innovative IDS to elevate IoT security. The proposed IDS boasts an impressive detection rate, exceeding 98%. This high accuracy instills confidence in its reliability. Furthermore, its lightning-fast response time, averaging under 1.2 s, positions it among the fastest intrusion detection systems available.

Internet of things (IoT)-based structural health monitoring of laboratory-scale civil engineering structures

Rapid advances in the Internet of Things (IoT) domain have made it a crucial technology for the real-time structural health monitoring (SHM) of civil engineering infrastructures. The availability of quick and accurate vibration data is essential for SHM, and such data can be obtained through IoT devices mounted on the structures. This study proposes a real-time damage prediction and localization approach using a low-cost "do-it-yourself" wireless sensor node with IoT capabilities for SHM. The proposed sensor node comprised a microcontroller (NODE MCU ESP8266) and a 6-axis accelerometer (MPU6050). The IoT devices track the real-time frequency of the laboratory-scale structure indirectly via measurement of acceleration-time history, and their results are compared with conventional industry-standard accelerometers. Promising results, with a <6% average difference from the conventional accelerometer (difference ranging from 1.3 to 14.3%), provided an innovative SHM for vibration-based real-time SHM using the IoT paradigm. The performance of the proposed methodology was validated numerically and experimentally on two laboratory-scale structures, and the potential of IoT technology for enhancing the efficiency of SHM was demonstrated. The proposed method thus can enable the early detection of damages in infrastructures such as buildings and bridges and thus can reduce the likelihood of accidents via continuous SHM.

Exploiting Traffic Light Coordination and Auctions for Intersection and Emergency Vehicle Management in a Smart City Mixed Scenario.

IoT (Internet-of-Things)-powered devices can be exploited to connect vehicles to smart city infrastructure, allowing vehicles to share their intentions while retrieving contextual information about diverse aspects of urban viability. In this paper, we place ourselves in a transient scenario in which next-generation vehicles that are able to communicate with the surrounding infrastructure coexist with traditional vehicles with limited or absent IoT capabilities. We focus on intersection management, in particular on reusing existing traffic lights empowered by a new management system. We propose an auction-based system in which traffic lights are able to exchange contextual information with vehicles and other nearby traffic lights with the aim of reducing average waiting times at intersections and consequently overall trip times. We use bid propagation to improve standard vehicle trip times while allowing emergency vehicles to free up the way ahead without needing ad hoc system for such vehicle, only an increase in their budget. The proposed system is then tested against two baselines: the classical Fixed Time Control system currently adopted for traffic lights, and an auction strategy that does not exploit traffic light coordination. We performed a large set of experiments using the well known MATSim transport simulator on both a synthetic Manhattan map and on a map we built of an urban area located in Modena, Northern Italy. Our results show that the proposed approach performs better than the classical fixed time control system and the auction strategy that does not exploit coordination among traffic lights.

Driver Identification and Detection of Drowsiness while Driving

This paper introduces a cutting-edge approach that combines facial recognition and drowsiness detection technologies with Internet of Things capabilities, including 5G/6G connectivity, aimed at bolstering vehicle security and driver safety. The delineated two-phase project is tailored to strengthen security measures and address accidents stemming from driver distraction and fatigue. The initial phase is centered on facial recognition for driver authentication before vehicle initiation. Following successful authentication, the subsequent phase harnesses continuous eye monitoring features, leveraging edge computing for real-time processing to identify signs of drowsiness during the journey. Emphasis is placed on video-based identification and analysis to ensure robust drowsiness detection. Finally, the study highlights the potential of these innovations to revolutionize automotive security and accident prevention within the context of intelligent transport systems.

“Park Easy” (IOT Based Parking System)

Parking management is a major challenge due to the increasing number of vehicles in cities. Traditional parking systems often lead to driver delays, inefficiency and frustration. To address these issues, this work proposes the development of an Internet of Things (IoT)-based system using infrared (IR) sensors for real-time monitoring and monitoring of parking lots on the proposed system uses IR sensors strategically placed in parking lots to detect the presence of vehicles. These sensors are connected to a central control unit equipped with IoT capabilities, enabling wireless communication and data exchange over the Internet. Through this network, real-time information about parking availability is transmitted via mobile applications or web platforms to an accessible user interface

Revolutionizing Somali agriculture: harnessing machine learning and IoT for optimal crop recommendations

Agriculture drives Somalia's economy, but challenges like unpredictable weather, limited resources, and poor infrastructure hamper productivity and economic progress. Emerging technologies like machine learning and IoT offer transformative solutions, optimizing crop yield and resource use. This research demonstrates the substantial impact of integrating Machine Learning (ML) and Internet of Things (IoT) technologies to improve agricultural decisions in Somalia. The study conducts a comprehensive comparison of Decision Trees (DT), K-nearest Neighbor (KNN), and Random Forest algorithms within a Crop Recommendation System. The Decision Tree algorithm emerges as the standout performer, boasting an impressive accuracy of 99.2% and achieving well-balanced precision, recall, and F1-score metrics. Its transparency and interpretability render it an optimal choice for guiding agricultural choices. Despite slightly trailing in performance, KNN and Random Forest algorithms achieve accuracies of 97.2% and 99.0% respectively, presenting valuable alternatives for various contexts. The successful implementation of the Crop Recommendation System, particularly in Somalia's Balcad District, underscores the tangible advantages of real-time IoT data and the Decision Tree model. This system enables farmers to optimize crop selection, thereby enhancing sustainability and yield potential. In a broader context, this research underscores the capacity of data-driven agriculture to tackle food security challenges and drive economic advancement. The transparent and accurate attributes of the Decision Tree algorithm, coupled with IoT capabilities, establish a framework for modernizing traditional farming practices and shaping a more productive future for Somalia and the global agriculture. The continuous evolution of crop recommendation systems holds promise for further transformative opportunities within the agricultural sector.