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International Conference on Smart Technologies For Smart Nation (SmartTechCon)

作者： R. Latha R. Ramya U. Arul Nilamadhab Mishra S. Dhanalakshmi Professor Department of Computer Science and Engineering K. Ramakrishnan College of Engineering Trichy Tamil Nadu India Department of Mathematics S.A Engineering College Chennai Tamil Nadu India Professor Department of Artificial Intelligence and Machine Learning Saveetha School of Engineering Saveetha Institute of Medical And Technical Sciences Chennai Tamil Nadu School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh India Assistant Professor Department of Electronics and Communication Engineering Sri Muthukumaran Institute of Technology Chennai Tamil Nadu India

The paper describes an innovative technique of monitoring updates on the health of people with dementia by integrating smart sensing technologies with a cloud-based platform. Because dementia is a degenerative neuropsychiatric disease that develops with time, constant patient monitoring is essential for ensuring the health and safety of those living with the condition. The proposed system uses smart sensing devices, including wearable and ambient sensors, to monitor dementia patients' health in real-time. Data like heart rates, movements used, and ambient conditions are collected and sent to a server in the cloud for analysis. The camera can monitor and analyze visual data, capture crucial information, and help evaluate the patient's well-being. Multiple patients can be monitored effectively in real time because of the cloud-based system's scalability, accessibility, and storage capacities. For healthcare providers to recognize irregular movements, identify possible risks to health, and implement preventative measures, doctors utilize the moment data analytics devices to gather valuable insights from the acquired data. In addition, the cloud-based solution improves collaborative care and enhances patient support by allowing for continuous communication and information sent among caregivers, doctors, nurses, and family members. Predefined thresholds or anomalous occurrences may trigger alerts and messages, allowing for quick action in reaction to emergencies. Modern technology and data analytics increase the health and happiness of people with dementia.

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An Efficient and Lightweight Intrusion Detection System for Mobile Ad Hoc Networks

An Efficient and Lightweight Intrusion Detection System for ...

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International Conference on Recent Advances in Design, Materials and Manufacturing, ICRADMM 2020

作者： Vali, Y. Sharmasth Prakash, N. Shakkeera, L. Research Scholar Department of Information Technology B. S. Abdur Rahman Crescent Institute of Science and Technology Tamil Nadu Chennai India Associate Professor Department of Information Technology B. S. Abdur Rahman Crescent Institute of Science and Technology Tamil Nadu Chennai India Associate Professor School of Computing Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789811640827

The distinctive aspects of Mobile Ad Hoc Networks (MANETs), including dynamic network topology, susceptible wireless medium, and limited battery power are highly vulnerable to various types of invasion. The traditional Intrusion Detection System (IDS) prevents the network from intruders using observation-based techniques and security algorithms. However, the limited battery power and network overhead is still a major issue to design an IDS. This paper proposes a Distributed and Cooperative Lightweight Intrusion Detection (DCLID) system to discern and eradicate the intruders from the network. The proposed system includes local detection engine, local analyzer, and trust management system. A local detection engine continuously monitors the network activity and stores the monitoring data in a table. A local analyzer examines the monitoring data periodically to evaluate a threshold based on network traffic and network connectivity. An extra field is added to a routing protocol to store the observed data for threshold measurement. The DCLID system is a lightweight system, it only turns on when the attack happens in the network and the network lifetime is high owing to lightweight designing. The threshold value measurement is used to trigger the IDS for detecting the intruders based on trust estimation. It estimates the trustworthiness of a node using Dempster–Shafer (DS) evidence theory. The DS theory provides a mathematical way to merge the observed data from different observers for deciding trustworthiness of an intruder. The simulation results demonstrate the efficacy of the DCLID system. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Dempster–Shafer theory First keyword Lightweight intrusion detection system MANET Network layer attacks Second keyword Third keyword Trust management

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Covid lockdowns in the UK: Estimating their effects on transmission

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Significance (Oxford, England) 2022年第2期19卷 14-18页

作者： Emily Prestige Julian Stander Yinghui Wei Holds a BSc (Hons) in mathematics and statistics from the University of Plymouth and this article is based on their final-year undergraduate project. They are currently undertaking an MSc in medical statistics at the London School of Hygiene & Tropical Medicine. Associate professor of mathematics and statistics at the School of Engineering Computing and Mathematics University of Plymouth. Associate professor of statistics at the School of Engineering Computing and Mathematics University of Plymouth.

UK citizens have lived through three lockdowns over the course of the Covid-19 pandemic. What effect have these restrictions had on the transmission of the virus? and investigate.

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Tuning Hyper Parameters of Deep Learning Model to Monitor Obstructive Sleep Apnea (OSA)

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Sleep Epidemiology 2022年 2卷 100031-100031页

作者： Anu, V. Maria Jagadeesh, Mandala Gladence, L. Mary Srinivasulu, Senduru Revathy, S. Rani, V. Nirmal Associate Professor SCOPE VIT Chennai UG Scholar Department of Electronics and Communication Engineering Associate Professor School of Computing Sathyabama Institute of Science and Technology Chennai India

Currently, a series of developing diseases in nations like India's powers to look for new answers to a continuing observation of health registry. Visiting emergency clinics has become a necessity. Even now for specialist's meeting, which has turned out to be monetarily related and a tedious procedure. Beside the above-mentioned lines, a non-stop checking of this problem is a primary need in medicinal offerings arrangements. There are some diseases which affects the quality of the lifestyle in a very slow manner. Sleep is considered to be most important activity in human day to day activities. During sleep most of the essential processes happens which benefits human body. Number of people affected by sleeping problems, is increasing due to current lifestyle. One such problem commonly found in humans is Obstructive Sleep Apnea (OSA). There are a few frameworks for OSA recognition. Hence, this exploration displays framework for both to acknowledge and help for the treatment of OSA of aged, home alone persons by observing various factors, like sleeping position, rest status, physical activities and physical parameters just as the utilization of open information accessible in smart urban communities. Our framework engineering performs two sorts of handling. From one perspective, a pre-preparing dependent on guidelines that empowers the sending of continuous notifications to the attendee, in case of a crisis circumstance. In this paper, we discuss various tuning parameters for constructing deep learning model by using the data received from the conducted experiments. © 2022 The Authors

关键词： Alert System Convolution Neural Networks Deep learning Internet-of-Things Obstructive Sleep Apnea

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Authentication mechanisms used in Wireless Body Area Networks: a study

Authentication mechanisms used in Wireless Body Area Network...

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The 3rd International Conference on Distributed Sensing and Intelligent Systems (ICDSIS 2022)

作者： P. Sharma K. S. Saini P. K. Sidhu Research Scholar University Institute of Computing Chandigarh University Mohali Punjab India Professor University Institute of Engineering Chandigarh University Mohali Punjab India Associate Professor IT Department MSIT GGSIP University New Delhi India

The WBANs (Collection of light-weight body sensor) of IOT and Cloud computing provides a substantial ability to upgrade the quality of on-demand health care system. Body Sensors are implanted within or outside the human being body to remotely measure the real-time parameters such as physiology signal and activity. The biggest issue originates from obtaining imprecise and inconsistent measurements when collecting these data from sensor nodes. Moreover, Privacy and Security of human sensitive information are other biggest hurdles of WBANs. In this chapter we describe some wearable devices, security requirements and some security attacks. Moreover, we also discussed various existing authentication mechanisms. Different authentication mechanisms have their own Pros and Cons. Further, based on the study we will performed some comprehensive overview between all existing authentication mechanisms and find some future scope. We also highlight some future research scope in the last section.

关键词： body area networks body sensor networks cloud computing data privacy health care Internet of Things telecommunication security telemedicine wireless sensor networks

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Precise Jump Planning using Centroidal Dynamics based Bilevel Optimization

Precise Jump Planning using Centroidal Dynamics based Bileve...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Ivo Vatavuk Zdenko Kovačić PhD Student at the Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia PhD is a Full Professor at the Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

This paper deals with a problem of precise jumping for legged robots: what are the control inputs required to perform a jump that results in a desired landing point? We propose a novel precise jump planning method, formulated as a bilevel optimization problem. The presented formulation exploits certain insights into the jump dynamics, leading to a low-dimensional optimization problem, and allowing fast computation. During the Flight phase of a jump there are no external forces other than gravity acting on the robot, so its centroidal angular momentum (CAM) is conserved, and its center of mass (COM) follows a ballistic trajectory. This trajectory depends solely on COM position and velocity at Liftoff. We define a bilevel optimization problem consisting of a nonlinear upper-level problem, and a lower-level quadratic programming (QP) problem. The upper-level problem selects COM position and velocity at Liftoff that result in a desired landing point, while minimizing CAM at Liftoff. The lower-level problem selects ground reaction forces during Push-Off that achieve desired COM position and velocity at Liftoff. The results are presented on a simulated one-legged robot, but the proposed approach can be extended to bipeds and multi-legged robots.

关键词： Legged locomotion Automation Conferences Dynamics Planning Trajectory Quadratic programming

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Applications of Artificial Intelligence in Biomedical Image Processing 2

Applications of Artificial Intelligence in Biomedical Image ...

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Rajeyyagari, Sivaram Hung, Bui Thanh Chakrabarti, Prasun Shaqra University College of Computing and Information Technology Department of Computer Science Shaqra Saudi Arabia Thu Dau Mot University Data Analytics and Artificial Intelligence Laboratory Engineering Technology Faculty Thu Dau Mot Viet Nam Provost and Institute Endowed Distinguished Senior Chair Professor Techno India Njr Institute of Technology Rajasthan India

ISBN: (纸本)9781665400527

The biomedical applications of nanoparticles are growing in recent years. The uses range from diagnostic to therapeutic purposes, and researchers are constantly introducing new ways. Biosensors, miniaturization techniques, surface enhancement in implantable biomaterials, and better nanofibers in medical textiles are some of the contributions of biomedical nanotechnology. Therapeutic (medical) imaging successfully maps the anatomy of the human body. Image enhancement, analysis, categorization, and image based representation are all possible areas of computer processing and analysis of medical images. Therapeutic image understanding uses computer vision, applied mathematics, signal analysis, and artificial intelligence to recognise objects in medical images. Image processing is the use of computer algorithms to manipulate digital images. Hand-held transducers emit and receive pulsed acoustic waves for medical ultrasound imaging. In this study, a computer-aided diagnosis method is developed to help cytotechnicians locate and classify aberrant cells in cervical cytology images. With the outcomes of morphological and statistical edge based segmentation are compared to traditional segmentation techniques. The proposed segmentation methodology outperforms the other methods. This proposed technique's segmentation accuracy is 98%. © 2022 IEEE.

关键词： Artificial intelligence

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Any Bluetooth device can be hacked. Know how?

Cyber Security and Applications

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Cyber Security and Applications 2024年 2卷

作者： Muraleedhara, Prathibha Christo, Mary Subaja J, Jaya Yuvasini  D College of Technology – Information Security and Program Management University of Houston 77204 TX United States Department of Networking and Communication School of Computing SRM Institute of Science and Technology Kantankulathur Chennai India Department of Electronics and Communication Engineering Hindustan College of Engineering and Technology India Assistant Professor Department of Computer Science and Business Systems Thiagarajar College of Engineering Madurai 625015 India

In today's world, Bluetooth technology is integrated into almost every device we use, from wireless headsets, mice, and keyboards to cars and smart home devices. But with the convenience of this technology comes the risk of privacy and security breaches. Each Bluetooth device has potential vulnerabilities that cybercriminals can exploit and take advantage of. It is important to create awareness about various Bluetooth vulnerabilities, exploits, and ways to prevent them. This article examines the dark side of Bluetooth technology by explaining how hackers can find ways to bypass the advanced security features of laptops, phones, cars, or smart home devices to compromise the devices and steal personal sensitive data. Whether it is a casual user of Bluetooth technology or a business owner with multiple devices, understanding these risks is crucial to protecting yourself and your information. This article begins by explaining the basics of Bluetooth technology and how it works. Followed by a list of security risks involved while using Bluetooth and finally, it highlights the best practices to protect the devices and the data they contain. © 2024

关键词： Ad hoc networks and security risk Bluetooth Exploit Threat Vulnerability

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Human-Computer Interaction: Innovations and Challenges in Virtual Reality

Human-Computer Interaction: Innovations and Challenges in Vi...

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International Conference on Science Technology engineering and Management (ICONSTEM)

作者： Cuddapah Anitha Prem latha Soundarraj N. Geethanjali C. Boopathy A. Narasima Venkatesh I. Mohana Krishna Department of Computer Science and Engineering School of Computing Mohan Babu University Erstwhile SreeVidyanikethan Engineering College Tirupati School of Business and Management Christ University Pune Lavasa Maharashtra Department of Management Studies PSNA College of Engineering and Technology Dindigul Tamil Nadu School of Management Studies Sri Krishna College of Engineering and Technology Kuniyamuthur Coimbatore Professor and Head of The Department HRM and General Management ISBR Business School Bangalore Karnataka India K L Business School KLEF Vaddeswaram Andhra Pradesh

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

In an effort to shed light on the advances and difficulties that are shaping the area of Virtual Reality (VR), this research paper digs into the ever-evolving world of Human-Computer Interaction (HCI) within the context of VR. We have found important insights with theoretical and practical applications via a careful research technique comprising mathematical modelling, data collecting, and empirical analysis. Through our investigation of new technologies, we have shown the revolutionary potential of haptic feedback systems in VR settings. Our results, backed by a solid mathematical model, provide light on the measurable effect of haptic feedback and suggest it has the potential to radically alter user experiences in fields as diverse as gaming, instruction, and treatment. At the same time, we have overcome a number of obstacles inherent to virtual reality human-computer interaction, including motion sickness. Our mathematical model of motion sickness and its treatment lays the groundwork for creating VR experiences that are both enjoyable and safe for a wider range of users. This study highlights the ethical implications of VR HCI, highlighting the importance of responsible development and deployment in addition to advances and problems. To make sure that the advantages of this gamechanging technology are used in a responsible manner, we discuss issues like privacy, informed consent, and the possibility for addiction in VR. Our results, as we reach the end of our trip, are both a celebration of potential and a guide for where VR HCI is headed. They motivate more research into inclusive and human-centered design, personalized motion sickness prevention, and cutting-edge haptic feedback technologies. To further lead the development of VR HCI, we advocate for continuous multidisciplinary cooperation and the adoption of thorough ethical rules and regulations.

关键词： Human computer interaction Ethics Technological innovation Solid modeling Virtual reality Motion sickness Solids

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IoT Based Human Biometric System Using Alcohol Level Detection for Driver Security

IoT Based Human Biometric System Using Alcohol Level Detecti...

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Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), International Conference on

作者： Anurag Sinha Nitish Kumar Amrita Ticku Vyom Modi Meghal Shah Kapil Shrivastava School of Computing and Information Sciences IGNOU New Delhi India Department of Computer Science Lovely Professional University Phagwara Punjab India Bharti Vidyapeeth's College of Engineering India India Faculty of Engineering Marwadi Education Foundation Rajkot Gujarat India Department of Computer Science & Engineering Charotar University of Science & Technology Gujarat India Assistant professor Department of computer engineering and applications GLA University mathura India

In today's society, driving after intoxication has become a major factor in traffic accidents. It is common knowledge that operating a vehicle while intoxicated is a major contributing factor in a significant number of accidents. The effects of drunk driving go beyond the drunk driver; they also affect other drivers and passengers in the same vehicle. As a result, this growing threat needs to be addressed immediately. Our project's goal is to create a system that uses the Internet of Things (IoT) to find traces of alcohol in someone's breath and apply preventive measures in order to effectively address this issue. Although there are laws against drunk driving, it is difficult to enforce them widely because law enforcement cannot constantly be present on the roads to spot drunk drivers. This restriction increases the chance of accidents significantly. In order to reduce future risks, a trustworthy system that can recognize and discourage drunk drivers is urgently needed. Drunk driving deaths are increasing, so we need to figure out how to reduce these kinds of deaths. The breath analyzing sensor used in the suggested system is the MQ-3, which calculates the breath alcohol content of an individual. The amount of alcohol that is allowed in the blood in India is 0.03. The engine won't start if the person's blood alcohol content is higher than this limit, making it impossible for them to drive. Additionally, the system will send an alert, possibly through a Raspberry Pi, to a friend or relative, providing the exact location using GPS coordinates. This notification serves as a precautionary measure to keep others informed about the situation. Implementing such a system can contribute significantly to reducing accidents related to alcohol consumption. In conclusion, detectors like the one proposed in this project hold immense significance in preventing the loss of life and property caused by reckless driving under the influence of alcohol.

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