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Smart Sports: Enhancing Physical Performance with IoT and Sensor Technologies

Smart Sports: Enhancing Physical Performance with IoT and Se...

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Automation and Computation (AUTOCOM), International Conference on

作者： Sudhanshu Dev Pavan P. S. Arifa Ahmed Neeraj Das Ishika Soni Prakash Chandra Sahoo Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Engineering and Technology Civil Engineering JAIN (Deemed to be University) Bangalore Karnataka India Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Smart Sports is a pioneering one that employs the Internet of Things (IoT) and sensor technology in optimizing physical performance for sports. Using connected wearables, equipment, and facilities, SmartPitch can collect real-time data for analyses that help improve training techniques and preinjury precautionary methods, leading to improved performance. Smart Sports gives a more complete look at an athlete's performance as the global application of IoT and sensor technology in sports continues to increase. Wearable technology, such as smart clothing, fitness bands, or GPS trackers, is capable of monitoring vital signs and physical information in real-time to assist coaches in analyzing everything relevant to an athlete. Smart Sports applications also include smart equipment and venues like Smart Home Courts or Pitches that are equipped with ball speed, trajectory & impact sensors to deliver instant quantitative feedback to coaches on player technique & performance. The information could be built upon to design a bespoke training program to suit that individual, providing an efficient and potentially very effective product. While the technology can improve player performance, Smart Sports are also used to predict injuries before they happen and give athletes or their coaches a headsup in real-time. IoT has the potential to ensure safer training, thus increasing an athlete's career longevity and quality of life. In general, smart sports can provide a data-driven and customized way to improve physical capacity, prevent injuries, and increase the chances of sporting success.

关键词： Training Smart textiles Smart homes Real-time systems Time measurement Trajectory Internet of Things Wearable devices Injuries Sports

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Tackling Big Data Challenges in Large Language Models with An Emphasis on Sharing, Security, and Scalability

Tackling Big Data Challenges in Large Language Models with A...

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International Conference on ICT in Business Industry & Government (ICTBIG)

作者： B Reddy Chethan M V. K. Kolekar G. Arun Francis Sorabh Sharma Maheshwari B Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Sciences Physics & Electronics JAIN (Deemed to be University) Bangalore Karnataka India Computer Engineering Vishwakarma Institute of Technology Pune India Department of Electronics and Communication Engineering Karpagam College of Engineering Coimbatore India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of EEE Prince Shri Venkateshwara Padmavathy Engineering College Chennai India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

This paper proposes a novel approach to huge data challenges in large language models (LLMs) that prioritises sharing, security, and scale. Our solution leverages modern encryption algorithms, distributed computing tools, and edge computing principles to secure data and speed up computers. We routinely outperform previous methods in accuracy, precision, memory, and model fitting rates. Our research found that the strategy protects private data, reduces interaction costs, and speeds up model training. Cutting-edge technology allows accurate forecasts and seamless computer operations in many contexts. Ablation studies also demonstrate how our approach's components work together to improve performance. This paper advances AI-driven LLMs by demonstrating a secure, affordable, and scalable method for today's data issues. Future research may concentrate on blockchain and shared learning's larger applications and advancements as data security and computer scale become more important. Our strategy is a huge step towards creating safe and dependable AI systems that can manage today's data-driven situations.

关键词： computers Accuracy Computational modeling Large language models Scalability Data security Big Data Data models Encryption Edge computing

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Biometric Sensors for Secure and Continuous Health Tracking in Healthcare Applications

Biometric Sensors for Secure and Continuous Health Tracking ...

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Automation and Computation (AUTOCOM), International Conference on

作者： Noel Prashant Ratchagar Trapty Agarwal Suhas Gupta Rina Mahakud Sidhant Das Spoorthi B Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Engineering and Technology Electrical and Electronics Engineering JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

In the healthcare domain, biometric sensors are indispensable, as they enable secure and continuous health monitoring. They can detect and acquire physiological information, including heart rate, blood pressure, and oxygen levels, in a non-invasive and very timely manner. They can then transfer this information over to a secured database, where further analysis can be carried out and the data integrated into healthcare applications. The provision of objective and accurate data is one of the main properties of biometric sensors, as human errors and biases involved in self-reports by patients can be avoided. It allows health authorities to have more data available when making true and immediate decisions about how to proceed in terms of taking care of patients. Biometric sensors also provide additional security features, ensuring that only authenticated individuals have access to sensitive health data. This problem is even worse within the healthcare industry, as data privacy and security should be of utmost concentration. This means biometric sensors are continuously monitored over time, so in the case of an issue, it can be detected early and tracked sequentially through treatment plans. It is particularly advantageous for patients with chronic diseases or individuals in rehabilitation.

关键词： Heart rate Data privacy Accuracy Medical services Blood pressure Biosensors Security Biomedical monitoring Monitoring Diseases

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Real-Time Indoor Localization Using IoT and Sensor Networks for Human Activity Monitoring

Real-Time Indoor Localization Using IoT and Sensor Networks ...

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Automation and Computation (AUTOCOM), International Conference on

作者： V Muthu Ganesh Intekhab Alam Dikshit Sharma Samuka Mohanty Yuvraj Parmar Gautham Krishna Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Engineering and Technology Department of Civil Engineering JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

To develop an effective real-time indoor localization methodology by exploiting the Internet of Things (IoT) consists of sensor networks. This tech is to support a more robust HAM application that allows for precise and continuous tracking based on individual locations inside buildings. It uses a combination of IoT devices and sensors to give people in the indoor environment real-time positioning data. Real-time indoor Localization based on IoT and Sensor Networks is a technology that allows evaluating precise continuous tracking of individuals in buildings to monitor human activity by applying advanced techniques such as Wireless sensor networks. Essentially, this technology leverages IoT devices and sensors to give precise real-time location information of people inside buildings. This accurate and reliable indoor positioning uses advanced techniques such as wireless sensor networks, lowenergy Bluetooth, and IoT technologies like RFID; this technology can be achieved only in Hospitals, shopping malls, and offices where it enables you to track human activities from indoor spaces at the current moment”Ǆ Installing sensors and IoT devices throughout the building connected to a central data center or via Natural Activity Limit Parametrization Real-time indoor localization using the Internet of Things (IoT) and sensor networks enables accurate tracking for human activity monitoring inside buildings. This technology uses IoT devices with sensors to give people precise real-time information on their location in an indoor space. This technology provides highly precise and reliable indoor positioning with advanced techniques such as wireless sensor networks, Bluetooth low energy, or RFID. The technology is best suited to tracking human activities in indoor spaces, including hospitals, shopping malls, and offices. This is followed by creating a data layer of network sensors and IOT devices inside the building connected to an on-premises or cloud central server. Sensors capt

关键词： Location awareness Wireless sensor networks Accuracy Hospitals Buildings Real-time systems Internet of Things Security Servers Monitoring

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Enhancing PCOS Prediction Accuracy Through Machine Learning Optimization

Enhancing PCOS Prediction Accuracy Through Machine Learning ...

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Data Science and Network Security (ICDSNS), International Conference on

作者： Kuldeep Sharma Raman Kumar Rajan Verma Amandeep Kaur Sanjeev Kumar Shah Mohemmed Hussien Centre of Research Impact and Outreach Chitkara University Rajpura Punjab India School of Mechanical Engineering Rayat Bahra University Mohali India Chitkara Center for Research and Development Chitkara University Himachal Pradesh India Department of Computer Science Engineering Chandigarh Engineering College Chandigarh Group of Colleges Jhanjeri Mohali India Department of Electronics & Communication engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun India The Islamic university Najaf Iraq

ISBN: (数字)9798350373110

ISBN: (纸本)9798350373127

In many countries around the globe, PCOS has been identified as one of the most common causes of infertility. This condition is characterized by hormonal imbalance, an irregular menstrual cycle, weight gain, excess acne, and many other symptoms. When left untreated, PCOS can lead to serious health problems such as sleep apnea, type-2 diabetes, obesity, heart disease, depression, and even suicide. Therefore, early detection of PCOS is crucial. An optimized narrow neural network (NNN) is proposed in this paper for the early prediction of PCOS. The model extracts clinical features from images, and hyperparameters of the NN classifiers are optimized to enhance prediction accuracy. The proposed model achieved 98.88% accuracy in extracting clinical features from images. Experimental results indicate moderate accuracy and low error rates for the proposed PCOS diagnosis method. The high accuracy and low error rates of the optimized NNN make it a suitable tool for real-time applications in PCOS diagnosis. The most accurate predictions are achieved by optimizing the hyperparameters of NN classifiers, demonstrating the potential of this method in early detection and effective management of PCOS.

关键词： Obesity Accuracy Sensitivity Error analysis Artificial neural networks Predictive models Feature extraction Sleep apnea Real-time systems Optimization

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Real-Time Tracking of Physical Activity and Exercise Performance with Wearable Sensors

Real-Time Tracking of Physical Activity and Exercise Perform...

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Automation and Computation (AUTOCOM), International Conference on

作者： Savitha R Manikandan T Dhananjay Kumar Yadav Sukhman Ghumman Anuradha Mohanta Sourav Rampal School of Engineering and Technology Electrical and Electronics Engineering JAIN (Deemed to be University) Bangalore Karnataka India Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

with increasing worldwide focus on the need for a healthy lifestyle, the provision of real-time tracking of physical activity and exercise performance has become critical in recent years. This makes traditional tracking methods, such as self-reporting or manual recording, ineffective and time-consuming. Technological innovations have made wearable sensors available that are capable of accurately measuring different physiological parameters during activity and exercise. Such as fitness trackers, heart rate monitors and smart watches that collect data on movement, heart rate and other biometric markers in real-time to measure the intensity and effectiveness of physical activity. It's this tracking in real-time, complemented with the ability to set targets and modify your exercise routines for improvements that you'll find valuable. Beyond the individual, wearable sensors have been used in group exercise contexts, delivering concurrent performance data to instructors, coaches and teams. This allows them to tailor the consultations and get the most out of every exercise.

关键词： Heart rate Performance evaluation Technological innovation Target tracking Accuracy Real-time systems Mobile handsets Biomedical monitoring Wearable sensors Monitoring

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Wearable Biosensors for Continuous Monitoring of Cardiovascular Health

Wearable Biosensors for Continuous Monitoring of Cardiovascu...

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Automation and Computation (AUTOCOM), International Conference on

作者： Adarsha H Prabhu Ankita Agarwal Anoop Dev Bubun Kumar Mohanta Prateek Garg School of Engineering and Technology Mechaical Engineering JAIN (Deemed to be University) Bangalore Karnataka India Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Wearable biosensors have revolutionized cardiovascular health monitoring. These body-fitted, continuous devices monitor a host of vital signs, including heart rate, blood pressure and oxygen levels. Such real-time monitoring will help detect and take prompt action in case the patient is at any risk of cardiac issues, further leading to a better quality of life and reducing serious illnesses. The non-invasive characteristic is one major benefit of wearable biosensors, as they can be worn day long very comfortably and easily. It also prevents the need for regular or emergency doctor visits and hospitalizations while saving money from healthcare bills with continuous monitoring as well. The biosensors are connected to a Smartphone or monitoring platform, helping healthcare professionals move the patient out of the tracking marquee area. This enables tailored and preventive care by allowing for instant correction of any anomalies. Aside from monitoring, wearable biosensors may play an important part, too. They can be integrated through other devices and also accurate health systems. How do they work? Biosensors for heart, \wearable's provide unprecedented convenience, accuracy and personalization\nor promoting and monitoring human cardiovascular health. The ability to continuously monitor patients in real-time has the potential to improve patient outcomes and transform health care significantly.

关键词： Heart rate Accuracy Medical services Transforms Real-time systems Blood pressure Biosensors Biomedical monitoring Monitoring Wearable sensors

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Optical Cross-Connect Technologies for Flexible Optical Networks 3

Optical Cross-Connect Technologies for Flexible Optical Netw...

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3rd IEEE International Conference on Automation and Computation, AUTOCOM 2025

作者： Aggarwal, Prateek Nanduri, Sireesha Poonguzhali, S. Singh, B.P. Aggarwal, Prateek Das, Satya Ranjan Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India Department of Computer Science and Engineering Odisha Bhubaneswar India

ISBN: (纸本)9798331542375

Various optical cross-connect technologies are being developed for flexible next-generation optical networks to ensure the efficiency of real-time optical network routing. Demand for larger bandwidth and faster data transmission continues to grow. Therefore, these networks are becoming more and more significant. Conventional optical cross-connects offer limited scalability, and they need to be more flexible by nature due to their traditional architecture, hindering fast adaptation to altering traffic patterns. A solution to this problem is the new OXC technologies, which allow dynamic and reconfigurable optical networks. These technologies use high-end optics and electronics, including wavelength-selective switches and coherent receivers, to offer routing and switching flexibility. One key benefit of flexible OXC technologies is that their capabilities to support different transmission formats and data rates cater well to specific service requisites. They also allow for greater implementation of software-defined networking principles, creating centralized control and management over the network. Moreover, flexible OXCs enable efficient tower best practices and O&M savings through reduced manual network intervention. © 2025 IEEE.

关键词： Bandwidth

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An Improved Digital Signal Processing for Signal Enhancement and Interference Mitigation 3

An Improved Digital Signal Processing for Signal Enhancement...

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3rd IEEE International Conference on Automation and Computation, AUTOCOM 2025

作者： Alam, Intekhab Baxi, Paramjit Sahoo, Barnali Garg, Mohan Roopashree, R. Thaj Mary Delsy, T. Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India Department of Computer Science and Engineering Odisha Bhubaneswar India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh Baddi174103 India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331542375

Digital Signal Processing has become a fundamental tool in signal processing applications, such as speech and image processing, due to its ability to manipulate and examine signals in a digital form skillfully. A primary challenge in signal processing involves the presence of unwanted noise and interference, which can negatively impact the precision and quality of the processed signal. The proposed advanced DSP approach aims to improve signal enhancement and interference mitigation techniques using sophisticated algorithms and methods. The proposed state-of-the-art DSP approach includes noise reduction algorithms, such as adaptive filtering and spectral subtraction, to eliminate unwanted noise from the signal. Additionally, cutting-edge signal processing techniques, such as wavelet transforms and time-frequency analysis, are used for signal enhancement and demising. The proposed approach employs adaptive equalization techniques to mitigate interference from other signals and substantially improve the overall signal quality. The enhanced DSP approach is evaluated through simulation and real-world experiments, demonstrating its effectiveness in improving signal quality and reducing interference considerably. The proposed approach has the potential to significantly improve the accuracy and reliability of various signal processing applications considerably, making it a valuable tool in fields such as telecommunications, audio and video processing, and medical signal analysis. © 2025 IEEE.

关键词： Image enhancement

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Integrated Photonic Routing and Switching for Scalable Optical Interconnects 3

Integrated Photonic Routing and Switching for Scalable Optic...

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3rd IEEE International Conference on Automation and Computation, AUTOCOM 2025

作者： Rajalakshmi, G. Agarwal, Ankita Kalra, Hitesh Potluri, Avinash Swadimath, Uma C. Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India Department of Computer Science and Engineering Odisha Bhubaneswar India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh Baddi174103 India Karnataka Bangalore India

ISBN: (纸本)9798331542375

The rapid increase in demand for higher data transfer rates and scalability, especially in data centers and other networks, has resulted in the emergence of Integrated Photonic Routing and switching technology for optical interconnects. IPRS uses integrated photonics, a technology that allows multiple photonic functions to be integrated on one chip to build scalable, high-speed optical networks. It replaces conventional electronic switches, constrained by system bandwidth and energy dissipation, with efficient, high-performance photonic switches. The IPRS system contains photonic router/switching units that route the data signals through different routing paths and finally switch them to the appropriate output port. A scalable photonic interconnect network that scales to interconnect without performance loss connects these units. It enables highly interoperable and flexible optical networks that can satisfy the increasing demand for data transmission. Likewise, integrated photonics are associated with numerous unique benefits in IPRS, such as decreased power consumption, more extensive bandwidth, and less delay than electronic interconnects. In addition, combining several photonic functionalities on a single chip leads to a small-size and low-cost solution that can be used to integrate thousands of chips into large-scale optical networks. This process to fabricate devices and integrated photonics receivers technology brings the potential for scalable on-chip high-speed optical interconnects and further addresses performance scalabilities cost-effectively, which is required in data centers, supercomputers and other high-performance networks. © 2025 IEEE.

关键词： Internet

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