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IoT-based smart alert system for drowsy driver detection
In current years, drowsy driver detection is the most necessary procedure to prevent any road accidents, probably worldwide. The aim of this study was to construct a smart alert technique for building intelligent vehicles that can automatically avoid drowsy driver impairment. But drowsiness is a natural phenomenon in the human body that happens due to different factors. Hence, it is required to design a robust alert system to avoid the cause of the mishap. In this proposed paper, we address a drowsy driver alert system that has been developed using such a technique in which the Video Stream Processing (VSP) is analyzed by eye blink concept through an Eye Aspect Ratio (EAR) and Euclidean distance of the eye. Face landmark algorithm is also used as a proper way to eye detection. When the drivers fatigue is detected, the IoT module issues a warning message along with impact of collision and location information, thereby alerting with the help of a voice speaking through the Raspberry Pi monitoring system. Copyright 2021 Anil Kumar Biswal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. -
IoT-Based Response Time Analysis of Messages for Smart Autonomous Collision Avoidance System Using Controller Area Network
Many accidents and serious problems occur on the road due to the rapid increase in traffic congestion in all sections of the country. Autonomous vehicles provide a solution to successfully and cost-effectively avoid this problem while minimizing user disruption. Currently, more engaging electromechanical elements with an analog interface are used to develop affordable automobiles for efficient and cost-effective operation for a smart driving platform with a semiautonomous automobile, strengthening the vehicle involvement of the driver while increasing safety. As a result, it takes longer for various car elements to respond, which causes more problems during message transmission. This project aims to create a Controller Area Network (CAN) for analyzing message response times by incorporating a few application nodes on the IoT platform, such as an antilock braking system, flexible cruise control, and seat belt section, for some real-time control system applications. These application nodes are car analytical parts that are linked to IoT modules to prevent collisions. An autonomous device for collision avoidance and obstacle detection in a vehicle can impact road accidents if the CAN protocol is implemented. 2022 Anil Kumar Biswal et al. -
IOT-BASED cyber security identification model through machine learning technique
Manual vulnerability evaluation tools produce erroneous data and lead to difficult analytical thinking. Such security concerns are exacerbated by the variety, imperfection, and redundancies of modern security repositories. These problems were common traits of producers and public vulnerability disclosures, which make it more difficult to identify security flaws through direct analysis through the Internet of Things (IoT). Recent breakthroughs in Machine Learning (ML) methods promise new solutions to each of these infamous diversification and asymmetric information problems throughout the constantly increasing vulnerability reporting databases. Due to their varied methodologies, those procedures themselves display varying levels of performance. The authors provide a method for cognitive cybersecurity that enhances human cognitive capacity in two ways. To create trustworthy data sets, initially reconcile competing vulnerability reports and then pre-process advanced embedded indicators. This proposed methodology's full potential has yet to be fulfilled, both in terms of its execution and its significance for security evaluation in application software. The study shows that the recommended mental security methodology works better when addressing the above inadequacies and the constraints of variation among cybersecurity alert mechanisms. Intriguing trade-offs are presented by the experimental analysis of our program, in particular the ensemble method that detects tendencies of computational security defects on data sources. 2023 The Authors -
IoT-Based automated dust bins and improved waste optimization techniques for Smart City
Effective waste management systems are essential for maintaining sustainability, environmental health, and cleanliness in the age of smart cities. This chapter provides a thorough analysis of the combination of cutting-edge waste minimization techniques with the deployment of an internet of things-based automatic dust bin. The suggested system optimizes garbage collection, lowers operating costs, and has a less environmental effect by combining the creative use of proximity sensors, real-time data analytics, and smart bin technologies. Remote monitoring and administration are made possible by the linked ecosystem that is created by the integration with the internet of things (IoT). In order to further promote environmentally friendly urban life, the study also examines waste-to-energy technology, circular economy ideas, and sustainable waste management techniques. The results provide insightful information for scholars, decision-makers, and urban planners looking for ground-breaking waste management solutions for today's cities. 2024, IGI Global. -
IoT Security with Blockchain Technology in the Financial Sector
Blockchain technology is to create immutable device IDs to stop identity faking whereas Internet of Things (IoT) is used in payment automation and to create smart payment systems. Both are evolving technologies, and their integration offers promising results in financial sector across the globe. Their combination holds a great deal of potential and is going to represent the next generation of smart finance technologies. But the major weaknesses that are present in IoT technologies includes those related to data security, privacy, device authentication, secure communication, and smart contract administration. This chapter focuses on the use of blockchain networks to regulate access and improve security in financial transactions, boost automation and improve efficiency of IoT applications. Blockchain and IoT integration in the financial industry provides a pathway to a more integrated, efficient, and secure financial environment. The chapter discusses the advantages of integrating IoT and Blockchain technologies in the financial sector and the challenges in its applications, and the regulatory mechanism thereof. 2025 Taylor & Francis Group, LLC. -
IoT networks: Integrated learning for privacy-preserving machine learning
Financial fraud is a persistent problem for consumers and financial institutions worldwide. It loses billions of dollars annually. Consequently, a strong fraud detection system (FDS) is essential to minimizing damage to financial institutions as well as clients. One common technique for spotting fraud is to use machine learning algorithms, which analyze large volumes of data to help with pattern detection and future prediction. It is difficult for a centralized FDS to detect fraud trends when these problems are coupled. To train a fraud detection model, this work presents a framework for federated learning, a machine-learning environment in which several entities collaborate to solve a machine-learning problem under the guidance of a central server or service provider. Also, the chapter examines how combined learning can be used to protect privacy in machine learning in Internet of Things systems. It focuses on four main calculations: federated averaging (FedAvg), secure aggregation, holomorphic encryption-based federated learning, and differential privacy in combined learning. Extensive experiments were carried out to evaluate these computations in terms of proving accuracy, conserving protection, and computing efficiency. The findings are shown in the results, with FedAvg achieving the highest accuracy of 92.5% and secure conglomeration demonstrating competitive precision levels of 91.8%. Calculations for differential privacy and holomorphic encryption demonstrated strong security conservation with very little data leakage and security parameters of 2.5 and 1.0, respectively. With little communication overhead and the ability to alter accuracy and conserve protection, secure aggregation emerged as a potential configuration. The computational productivity assessments revealed that secure accumulation produced little communication overhead despite its strong security conservation, which makes it suitable for IoT scenarios with limited resources. By using this tactic, financial institutions may avoid sharing datasets and benefit from a shared model that has seen more fraud than any one bank has on its own. Thus, the sensitive data of the user is protected. The results of the chapter indicate that the federated model (federated averaging) may be as good as or better than the central model (multi-layer perceptron) in detecting financial fraud. This chapter adds to the growing conversation around mixed learning in the Internet of Things by providing insights into the trade-offs between accuracy, security, and efficacy and by laying the groundwork for future developments in privacy-preserving machine learning standards. 2025 selection and editorial matter, Ahmed A. Elngar, Diego Oliva and Valentina E. Balas. All rights reserved. -
IoT innovation in COVID-19 crisis
The COVID-19 pandemic is a current global threat that surpasses provincial and radical boundaries. Due to the onset of the pandemic disease, the whole world turned entirely in a couple of weeks. Its consequences have come across the personal and professional life of human beings. The current situation focuses on precautions such as wearing a mask, maintaining social distancing, and sanitizing hands regularly. An innovative platform, and smart and effective IoT technology may be applied to follow these steps. This platform fulfills all critical challenges at the time of lockdown situations. IoT technology is more helpful in capturing real-time patient data and other essential information. IoT allows the tracing of infected people and suspicious cases and helps diagnose and treat patients remotely. It also paves the way to deliver essential medical devices and medicines to quarantined places. In the present ongoing crisis, IoT technology is inevitable in monitoring patients infected with COVID-19 through sensors and intertwined networks. The consultations are given to the patients digitally through video conferencing without meeting the medical expert in person. After the diagnosis is made digitally, IoT devices are used to track health data. Smart thermometers are used instead of traditional ones to collect valuable health data and share it with experts. The IoT robots are now a proven technology used for cleaning hospitals, disinfecting medical devices, and delivering medicines, thus giving more time to healthcare workers to treat patients. 2023 Bentham Science Publishers. All rights reserved. -
IoT Infrastructure to Energize Electromobility
Mobile technology is becoming more sophisticated as it advances. A comparison of different mobility scenarios was conducted. This chapter examined how electric vehicles interact with local energy systems in Stuttgart. Utilizing a travel demand model, a charging profle based on mobility patterns was generated for electric vehicles. During a quarter, charging demand and standard household load profles were used to analyze peak hour load fow for 349 households. Considering that peak loads and charging capacity are usually separated in time, greater charging capacity might lead to lower utilization of transformers. Furthermore, a study was conducted to determine if the existing infrastructure was adequate for future demand, focusing on substation transformer reserves. Electromobility is a rapidly growing and evolving application domain of the Internet of Things, with a huge market potential in various areas. It incorporates many stakeholders from manufacturers to the players of the energy market with all sorts of physical and virtual resources. It is essential to allow these devices and systems to collaborate to create advanced e-mobility services. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
IoT in schools: Revolutionizing education through smart technology
The Internet of Things (IoT) is rapidly transforming various sectors, and education is no exception. This chapter explores the potential and applications of IoT technology in the education sector, shedding light on how it can revolutionize teaching, learning, and overall school management. By seamlessly integrating smart devices and applications into the classroom environment, IoT creates an interconnected and efficient learning ecosystem. The discussion covers the current state of IoT adoption in education, highlighting the benefits, challenges, and future prospects of this technological integration. 2025 selection and editorial matter, Adesh Kumar, Surajit Mondal, Gaurav Verma, and Prashant Mani; individual chapters, the contributors. -
IoT Framework, Architecture Services, Platforms, and Reference Models
Internet of things (IoT) is spawning a twirl in the world of connected devices by aiding the devices to connect, compute, and coordinate with each other. While the concept of IoT is still embryonic, its outcomes are trailblazing. IoT acts as a facilitator in creating a smart world by connecting devices through sensors and actuators to the Internet. The acceptance of IoT in various sectors indicates that the partakers in an IoT ecology are diverse. This demands common functionalities, interoperability standards, and network protocols across sectors. But there exists an extremity of incongruency in devices, capabilities, and network protocols, and therefore it is imperative to have a complete reference architecture model that necessitates the existing diversities and defines a new monody for the IoT environment. The lack of standard and uniform architectural knowledge, frameworks, and platforms is presently resisting the researchers to reap the benefits that the Internet of things (IoT) offers. This chapter summarizes various Internet of things frameworks, architectures, platforms, and reference models and thereby paves way for businesses to build IoT on it. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
IoT enabled lung cancer detection and routing algorithm using CBSOA-based ShCNN
The Internet of Things (IoT) has tremendously spread worldwide, and it influenced the world through easy connectivity, interoperability, and interconnectivity using IoT devices. Numerous techniques have been developed using IoT-enabled health care systems for cancer detection, but some limitations exist in transmitting the health data to the cloud. The limitations can be accomplished using the proposed chronological-based social optimization algorithm (CBSOA) that effectively transmits the patient's health data using IoT network, thereby detecting lung cancer in an effective way. Initially, nodes in the IoT network are simulated such that patient's health data are collected, and for transmission of such data, routing is performed in order to transmit the health data from source to destination through a gateway based on cloud service using CBSOA. The fitness is newly modeled by assuming the factors like energy, distance, trust, delay, and link quality. Finally, lung cancer detection is carried out at the destination point. At the destination point, the acquired input data is fed to preprocessing phase to make the data acceptable for further mechanism using data normalization. Once the feature selection is done using Canberra distance, then the lung cancer detection is performed using shepard convolutional neural network (ShCNN). The process of routing as well as training of ShCNN is performed using the CBSOA algorithm, which is devised by the inclusion of the chronological concept into the social optimization algorithm. The proposed approach has achieved a maximum accuracy of 0.940, maximum sensitivity of 0.941, maximum specificity of 0.928, and minimum energy of 0.452. 2022 John Wiley & Sons Ltd. -
IoT Enabled Energy Optimization Through an Intelligent Home Automation
The benefit of IoT devices is that they allow for automation; nevertheless, billions of connected devices connected with one another waste a substantial amount of energy. IoT systems will have difficulty in wide adoption if the energy requirements are not adequately managed. This study proposes a solution for IoT devices to regulate their energy consumption. Both hardware and software aspects are taken into consideration. Using a mobile computer or smartphone with Internet connectivity to interact with actual scenarios has grown more prevalent as technology has advanced over the years. An intelligent home automation system based on android applications has been developed to save electricity and human energy. This study aims to create comprehensive Energy optimization through intelligent home automation utilizing widely available mobile applications and Wi-Fi technologies. The devices are turned on and off using Wi-Fi. Intelligent home, in the area of electronics, automation is the most purposely misused term. Numerous technological revolutions have occurred as a result of this demand for automation. These were more essential than any other technologies due to their ease of use. These can be used in place of household current switches, resulting in sparks and, in rare instances, such as fires. A unique energy optimization system was developed to control household appliances while taking advantage of Wi-Fi benefits. 2023, Bentham Books imprint. -
IOT driven automated water quality monitoring and removal of unpleasant smell from wastewater system for smart city /
Patent Number: 202241015394, Applicant: Geetha V.
Water pollution has become one of the most serious threats in recent years, as drinking water has become contaminated and polluted. Polluted water can cause a variety of diseases in humans and animals, affecting the ecosystem's life cycle. If water pollution is detected early on, appropriate measures can be implemented, and critical situations can be avoided. To ensure a steady supply of pure water, the water's quality should be monitored in real time. With advancements in sensors, communication, and Internet of Things (IoT) technology, smart solutions for monitoring water pollution are becoming increasingly important. -
IOT Contribution in Construct of Green Energy
Energy derived from natural sources, such as sunlight, wind, and water, is called green energy. Green energy is a source of energy derived from clean sources such as solar, wind, geothermal, and biomass. The environment benefts from green energy because green energy replaces the harmful effects of fossil fuels with more environmentally friendly options. Green energy sources release far fewer greenhouse gases, as well as little or no air pollutants when looked at in their full life cycle. Taking steps to reduce air pollution benefts not only the planet but also human and animal health. Increasing reliance on the Internet of Things (IoT) has helped modernize the energy industry. Sensor attached to generation, transmission, and distribution equipment is used in IoT applications in green energy production. Alternative energy offers several benefts over traditional energy options. As the demand for clean energy grows and environmental prudence becomes the norm, Internet of Things solutions for energy management keep developing. Using the Internet of Things today benefts green energy, enabling companies in this sector to make the most of their data, and improves effciency and safety. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
IoT Cloud Systems: A Survey
IoT has gained a massive prevalence in the last decade. Various businesses are leveraging IoT Applications for industrial and commercial use cases. IoT also presents use cases in research and academia. However, setting up IoT Systems is complex due to the distributed and multi-disciplinary nature of IoT Systems. As a direct consequence of this complexity, the entire service industry has emerged that assists users to deploy and manage IoT systems. This paper aims to survey some of the Cloud management systems that help simplify and shorten the deployment process of IoT Systems. 2023 IEEE. -
IoT Based Water Management Using HC-12 and Django
Water is one of the important needs for a human being. Life on Earth is possible due to the presence of water on its surface. Even though 71% of Earth's surface is covered with water, the availability of water in certain areas is very less. So, the people in these areas must reserve water for ensuring a steady availability. These problems can be rectified with the help of Internet of Things (IOT). IOT is a global infrastructure with certain standards and communication protocols by which virtual and physical things can interact and exchange data by connecting to each other. In this paper, we propose a system for monitoring the availability of water, based on the water level in the storage system. Water level is measured with the help of a waterproof ultrasonic sensor and when the level reaches a threshold value, a notification is sent to the user or to the vendor to take the necessary action. The live feed data is sent to a relational database for storing and analyzing the data to predict when the water will run out, and to make sure that the water storage system gets refilled before that point of time. After processing the raw data from the sensors, the system can generate a fusion chart that can show or indicate the amount of water inside each storage system. With this, the user can have an idea of how much water is left in each of the storage system. The main aim of the proposed system is to showcase the functionalities and uses of different sensors and modules used in an IOT based system with the application of Wireless Sensor Network (WSN). In this present scenario, the world is filled with data both relevant and irrelevant, wherein the data for predicting a water crisis is less. So, through the proposed system we are generating a dataset for the prediction of a water crisis in an organization or a community. 2019 IEEE. -
IoT based Smart Poultry to Produce a Healthy Environment
According to studies, there are approximately 850 million poultry birds across India, with an average of 30 million farmers working in the sector. In other words, a poultry farm is a trustworthy and long-term way to make money in India. However, managing a poultry farm is labour intensive due to the need for constant surveillance and control over a wide range of environmental factors. The actual implementation of this is significantly more complicated, expensive, and time-consuming. The paper suggested a smart poultry system that tries to provide the solution for all the issues. The health of poultry birds heavily relies on environmental parameters, so variables like temperature and humidity are measured and monitored continuously. The website was made so that poultry keepers may get reliable information about their birds' health and use that information to take the appropriate measures. Moreover, in the event of a crisis, such as a fire or the illness of a single bird, the owner will receive a notification. It is also possible to gather information about the poultry in the specified timespan. The Firebase cloud is used for wireless monitoring and managing the poultry system. The suggested automatic smart poultry system will make the birds healthy and it indirectly helps the owners to increase their profit with minimal human effort. 2022 IEEE. -
IOT based smart green house system /
Patent Number: 202111031077, Applicant: Dr. Vikas Kumar.
The Smart Green House concept has been brought into the agricultural area to promote plant development in a short period of time. With an IoT-enabled framework controlled by a Smart Green House Intelligence Decision Support System, the system's quality can be improved. The system uses multiple sensors strategically positioned throughout a greenhouse to make decisions about actions such as water supply and nutrition level. All of the sensors and control systems operate in an automated setting, allowing small farmers to benefit from the greenhouse technology. -
IOT based smart energy theft detection and power monitoring system for smart homes /
Patent Number: 202141035598, Applicant: Dr. Poornima G.
Energy is the essential utility needed. Thus, the management of energy use is a significant priority, as the enormous growth changes are sweeping the globe, and doing so is the best answer, beginning domestically. There are numerous difficulties in the existing home energy meter reading systems, such as construction problems, too little bandwidth, poor real-time, no fast two-way communication, etc. Therefore, based on wireless internet technology, a smart meter is suggested. An Arduino microcontroller and raspberry pi CPU are used for the suggested smart energy meters for house management. -
IOT Based Smart Agriculture System
Smart agriculture is an emerging concept, because IOT sensors are capable of providing information about agriculture fields and then act upon based on the user input. In this Paper, it is proposed to develop a Smart agriculture System that uses advantages of cutting edge technologies such as Arduino, IOT and Wireless Sensor Network. The paper aims at making use of evolving technology i.e. IOT and smart agriculture using automation. Monitoring environmental conditions is the major factor to improve yield of the efficient crops. The feature of this paper includes development of a system which can monitor temperature, humidity, moisture and even the movement of animals which may destroy the crops in agricultural field through sensors using Arduino board and in case of any discrepancy send a SMS notification as well as a notification on the application developed for the same to the farmer's smartphone using Wi-Fi/3G/4G. The system has a duplex communication link based on a cellularInternet interface that allows for data inspection and irrigation scheduling to be programmed through an android application. Because of its energy autonomy and low cost, the system has the potential to be useful in water limited geographically isolated areas. 2018 IEEE.