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检索条件"任意字段=2017 International Conference On Smart Technology for Smart Nation, SmartTechCon 2017"

共 4139 条记录，以下是41-50 订阅

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The smart Factory of Tomorrow: Artificial Intelligence and Machine Learning Reshaping Manufacturing Processes

The Smart Factory of Tomorrow: Artificial Intelligence and M...

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international conference on smart Technologies For smart nation (smarttechcon)

作者： Priyanga P S. Sridevi Ashwini K Deepa S R Department of Artificial Intelligence and Machine Learning RNS Institute of Technology Bangalore Karnataka India Department of Computer Science and Engineering Vels Institute of Science Technology & Advanced Studies (VISTAS) Chennai Tamil Nadu India Department of Computer Science and Design K.S. Institute of Technology Bangalore Karnataka India

The smart factory of the future would not be possible without the development of AI and ML technologies, which have ushered in a new era of production. Traditional industrial processes are being revolutionized by AI and ML due to their capacity to evaluate large quantities of data and make autonomous choices, which is leading to greater efficiency, productivity, and profitability. Predictive maintenance is one area where AI and ML are making important contributions. These systems may prevent unexpected and expensive failures by constantly monitoring equipment performance and analyzing real-time data. Taking preventative measures like these results in less downtime, lower maintenance expenses, and more efficient machinery. Synergies between AI and ML are improving factory quality assurance. These technologies can identify even the smallest flaws or deviations from product standards using sophisticated vision systems and pattern recognition algorithms. Manufacturing companies may reduce waste and customer complaints by maintaining a constant quality standard via the use of automated inspection methods. Optimization of production planning and scheduling is another important use of AI and ML in manufacturing.

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The smart analysis of cell damage and cancerous prediction using information clustering model

The smart analysis of cell damage and cancerous prediction u...

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international conference on smart Technologies For smart nation (smarttechcon)

作者： Vinay Mallikarjunaradhya Jinal Mistry Ashween Ganesh T. Kiruthiga Legal Tech Platform Thomson Reuters Toronto Canada Medtronic Inc USA Research and Development Fresenius Meidical Care North America Concord CA Department of ECE Vetri Vinayaha College of Engineering and Technology Tricy Tamil Nadu India

with the assistance of Information Clustering Algorithm, the smart analysis of cellular damage and cancerous prediction is becoming easier and much more accurate over time. This algorithm has the potential to change the way medical research is conducted and its results used to predict cancer, as it produces more accurate and timely data regarding cellular damage on a molecular level. By utilizing this algorithm, researchers are able to detect changes in cellular information that have been correlated with the development of cancerous cells, as well as cellular damage caused by external factors such as radiation exposure and environmental factors. In addition, the algorithm can be used to analyze the molecular structure of existing cells and to detect whether they are at risk of malignant transformation. This allows for more precise diagnosis and treatment of cancer, and also helps to better understand the underlying causes of cancer. Furthermore, this algorithm can help identify new targets for drug therapy and also present promising avenues for further research regarding cancer and its causes.

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AI Enabled Digital Twin Models to Enhance Security in smart Cities

AI Enabled Digital Twin Models to Enhance Security in Smart ...

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2024 international conference on Intelligent Computing and Sustainable Innovations in technology, IC-SIT 2024

作者： Mayan, Aamir Krishanveni, S. Jothi, B. SRM Institute of Science and Technology KTR Deparrtment of Computational Intelligence Chennai India

ISBN: (纸本)9798350369175

As smart cities continue to expand, the security of interconnected systems, such as smart grids, water distribution, and waste management, is paramount. Traditional security measures often lack the predictive capabilities needed to identify and counter cyber threats effectively, posing risks to these critical infrastructures. This research investigates the use of AIenabled digital twin models to strengthen security in smart city environmental management systems. Utilizing Autodesk Tandem as the digital twin platform, we simulate these subsystems and integrate a machine learning (ML) model to monitor network fluctuations, simulate cyber-attacks, and evaluate response strategies. Specifically, a Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model, trained on the CICIDS2017 dataset, is applied to detect threats in real time. By observing subsystem behavior under attack conditions, we identify vulnerabilities and develop enhanced preventive measures. This approach seeks to create a robust security framework capable of predicting, detecting, and mitigating cyber threats in smart city infrastructures. © 2024 IEEE.

关键词： Cyber attacks

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An Efficient and Robust Explainable Artificial Intelligence for Securing smart Healthcare System*

An Efficient and Robust Explainable Artificial Intelligence ...

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international conference on smart Technologies For smart nation (smarttechcon)

作者： Tamizharasi Seetharaman Vandana Sharma Balamurugan B Veena Grover Alka Agnihotri Department of CSE CMR University Bangalore Computer Science Department CHRIST (Deemed to be University) India Shiva Nadar University India School of Management Noida Institute of Engineering & Technology India School of Business Galgotias University India

The advent of IoT technologies has a tremendous impact on the healthcare sector enabling efficient monitoring of patients and utilizing the data for better analytics. Since every activity related to a patient’s health is monitored, the focus on smart healthcare applications has significantly transferred from service provision to a security perspective. As most healthcare applications are automated security plays a vital role. The technique of machine learning has been widely used in securing smart healthcare systems. The major challenge is that these applications require high-quality labeled images, which are difficult to acquire from real-time security applications. Further, it highly time-consuming and cost-expensive process. To address these constraints, in this paper, we define an efficient and robust explainable artificial intelligence technique that takes a small quantity of labeled data to train and de-ploy the security countermeasure for targeted healthcare applications. The proposed approach enhances the security measure through the detection of drifting samples with explainability. It is observed that the proposed approach improved accuracy, high fidelity, and explanation measures. Also, this approach is proven to be considerably resistant against numerous security threats.

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Rural Automatic Healthcare Dispatch with Real-Time Remote Monitoring

Rural Automatic Healthcare Dispatch with Real-Time Remote Mo...

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international conference on smart Technologies For smart nation (smarttechcon)

作者： Chitra Sabapathy Ranganathan Ujwal Prabhakar Nandekar Ramakrishnan Raman C. Srinivasan Rachit Adhvaryu Mphasis Corporation Chandler Arizona USA Symbiosis Law School (SLS) Pune Symbiosis International (Deemed University) Pune Maharashtra India Symbiosis Institute of Business Management Pune & Symbiosis International (Deemed University) Pune Maharashtra India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Faculty of Engineering and Technology Parul Institute of Engineering and Technology Parul University Vadodara Gujarat India

Due to the drastically expanding use of the Internet of Things, remote monitoring of health data to provide intelligent healthcare has recently attracted much interest within the system. Health Chain is a massively-scale, blockchain-based privacy-preserving system for health data that uses encryption to provide fine-grained access control. The 24/7 Medical Counter is used in all rural areas when people have limited options to get in touch with an authorized medical professional. The proposed system is also connected to a camera, a headphone, an ultrasonic sensor, and a load cell. Additionally, set up a heart rate and temperature monitor. Utilized the medical counter and monitored from a distance. Both ends have a program installed that enables voice connection and doctor chat. Medication dispatchers provide medicine from Anytime Medical Machine (AMM) to users as doctors examine patients and write prescriptions. In order for the user to receive the precise time, they might make a request to the server.

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Design and Development of a User-Friendly, smart, and Assistive Kitchen for the Mauritian Elderly

Design and Development of a User-Friendly, Smart, and Assist...

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international conference on smart Technologies For smart nation (smarttechcon)

作者： Yovesh Bhiwoo Santaram Venkannah Sabrina Iranah-Ramsamy Department of Mechanical and Production Engineering Faculty of Engineering University of Mauritius Réduit Mauritius Academy of Design and Innovation Ebene Mauritius

The integration and adoption of smart home automation in common households are now no longer unusual. smartphones, smart appliances, and smart sensors can now communicate with AI-embedded devices such as Amazon Alexa, and Google Nest, to execute a command, schedule a meeting, call someone, or check on someone in the house with minimum effort and costs. However, despite all these perks available in the smart home automation advancement world, there is still the absence of smart age-related system development for seniors, particularly those who are living independently and have a vague understanding of technology. In comparison to the different age groups, the proportions of seniors are generally higher. Throughout the world, 46% of senior citizens have struggles while performing their daily grinds such as cooking, and in Mauritius, a small island developing state located on the East coast of Madagascar, the expanding population of the elderly are not spared where the percentage of seniors is rising swiftly and is anticipated to rise from 19% of the total population in 2023 to 26% by 2040. Undoubtedly it would be a game-changer in Mauritius if the current devices could be examined and made to meet the needs of elders while carrying out their everyday activities, particularly cooking. Therefore, this paper presents a smart kitchen designed for the Mauritian elderly, using Amazon Alexa, a voice assistant that is used to communicate with the seniors in the Mauritian native language to execute given commands and ensure the security of the seniors through various design solutions.

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smart Biking: IoT-Connected Cycling Gear for Training and Safety

Smart Biking: IoT-Connected Cycling Gear for Training and Sa...

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international conference on smart Technologies For smart nation (smarttechcon)

作者： S. Mohan Kumar Aparajita Mohanty Ramakrishnan Raman M. Muthulekshmi Amit Barve Research and Innovations CMR University Bangalore India Symbiosis Law School (SLS) Pune Symbiosis International (Deemed University) Pune Maharashtra India Symbiosis Institute of Business Management Pune & Symbiosis International (Deemed University) Pune Maharashtra India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Faculty of Engineering and Technology Parul Institute of Engineering and Technology Parul University Vadodara Gujarat India

Cycling has become popular due to urbanization, fitness, and eco-friendly transportation. The new idea, "smart biking," uses the Internet of Things (IoT) to link bikers to their equipment and surroundings to improve safety and pleasure. It discusses IoT-connected bicycle gear to enhance training and rider safety. A network of sensors in helmets, bicycles, and wearables with a smartphone app makes up smart Biking. IoT sensors monitor speed, heart rate, ambient conditions, and possible risks in real-time. Cyclists get individualized training insights, route optimization, and real-time safety warnings from the data. smart Biking designs workouts for each fitness level and objective. Progress is tracked to assist riders in maximizing training. Gaming promotes pleasant competition and social engagement, building a cycling community. smart Biking prevents accidents in several ways. Monitoring ambient elements and rider behavior may warn and prevent collisions. After an accident, the system may notify emergency services and give location data. smart Biking, which follows the IoT trend in sports and fitness, offers riders a unique and safe way to improve their experience. smart Biking will make riding safer and more fun for all levels as it becomes increasingly widespread as a source of transportation and entertainment.

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Securing Pedestrian Crosswalks in smart Cities: An Embedded Vision System for Pedestrian Detection and Safety Enhancement

Securing Pedestrian Crosswalks in Smart Cities: An Embedded ...

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international conference on smart Technologies For smart nation (smarttechcon)

作者： S. Mohan Kumar S. Prabagar Elangovan Guruva Reddy N. Latha S. Chandramohan Professor and Director Research and Innovations CMR University Bangalore Karnataka India Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bangalore India Department of Artificial Intelligence and Data Science Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Electronics and Communication Engineering Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University (Deemed University) Kanchipuram Tamil Nadu India

One of the most severe issues in the context of rapidly growing intelligent cities is the safety of pedestrians at urban crosswalks. To address this issue, the system developed an embedded vision system for real-time pedestrian detection and to enhance safety at crosswalks. A camera module captures real-time video, an image processor analyzes the captured data using a pedestrian detection algorithm, and a microcontroller manages the system's other functions. Our system can accurately identify pedestrians inside the crossing area using deep learning-based object detection models. If pedestrians are detected, an LED warning system alerts drivers to either slow down or stop, drastically decreasing the possibility of an accident. A real-time pedestrian count and any applicable safety warnings are also shown on an LCD screen. By connecting with existing systems, this smart technology may significantly improve the security of smart cities for pedestrians. Preliminary testing has demonstrated the technology has great potential for deployment in real-world urban environments.

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Blockchain Based Abstract Syntax Tree to Detect Vulnerability in IOT-Enabled smart Contract

Blockchain Based Abstract Syntax Tree to Detect Vulnerabilit...

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international conference on smart Technologies For smart nation (smarttechcon)

作者： Amit Mittal Gunawan Widjaja Renzon Daniel Cosme Pecho R. Kiruba Jesus Marino Falcón Roque Alok Chandra Department of Allied Science Graphic Era Hill University Bhimtal Faculty of Law Universitas 17 Agustus 1945 and Faculty of Public Health Universitas Indonesia Department of Biochemical Universidad San Ignacio De Loyola (USIL) Lima Peru Sri Ramakrishna Engineering College Coimbatore Department of Environmental Engineering Universidad San Ignacio de Loyola La Molina Lima Peru Lajpatrai Institute of Management Mumbai Mumbai University

As blockchain technology and the Internet of Things (IoT) have advanced, smart contracts have found new uses in many industries. Ethereum has become the go-to system for smart contract development. However, major financial losses have come from the ubiquity of smart contract vulnerabilities. Existing techniques have struggled to make efficient use of the syntax information in contract source code, making the detection of these vulnerabilities a key field of research. The reentrancy flaw in smart contracts is addressed by proposing a new vulnerability detection tool called SC-Defender . The abstract syntax tree representation of the source code for a smart contract written in the Solidity language is the core focus of SCDefender 's deep learning technique. Its efficient vulnerability identification is the result of its use of a tree-based convolutional neural network. In order to remove superfluous branches while keeping the essential ones, we develop a pruning technique for abstract syntax trees. The vulnerability detection findings achieved by SC-Defender are encouraging, with a precision of 81.43 percent, a recall of 92.12 percent, and an F1-score of 86.4 five percent. The results of the abolition experiments show that the abstract syntax tree pruning technique is a crucial part of SC-Defender 's ability to find vulnerabilities. These improvements in smart contract vulnerability detection, especially in the context of IoT-enabled smart contracts, have a lot of potential to make smart contracts safer and reduce the economic risks that come with their broad use.

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smart Personal Protective Equipment in Ambulance Services with IoT Integration for Safety

Smart Personal Protective Equipment in Ambulance Services wi...

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international conference on smart Technologies For smart nation (smarttechcon)

作者： R. Senkamalavalli Chethan Chandra S Basavaraddi L. M. Merlin Livingston N. Latha Elangovan Guruva Reddy Department of Computer Science and Engineering Kammavari Sangham Institute of Technology Bangalore Karnataka India Department of Computer Science and Engineering Kalpataru Institute of Technology Tiptur Tumkur Karnataka India Department of Electronics and Communication Engineering Jeppiaar Institute of Technology Chennai Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Artificial Intelligence and Data Science Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

Internet of Things (IoT) technology has improved ambulance safety and efficiency. In ambulance services, smart PPE (Personal Protective Equipment) improves patient and healthcare worker safety via IoT connectivity. In crises, ambulances are vital. However, healthcare professionals risk contagious infections and physical damage. Though vital, traditional PPE lacks real-time monitoring and communication, leaving healthcare workers exposed. These issues are addressed with smart PPE using IoT. This novel invention adds sensors and communication devices to paramedic and EMT PPE. These sensors measure air quality, temperature, and the wearer's heart and body temperature. A centralized system can remotely monitor healthcare personnel's safety and well-being using real-time data. smart PPE has two-way communicators and emergency alert systems. Emergency coordination is improved by ambulance crews and dispatch centers communicating seamlessly. The smart PPE can automatically inform the team and dispatch in urgent situations, increasing response times and patient outcomes. IoT enables predictive maintenance and data analytics. Trends and dangers may be identified from gathered data, allowing proactive risk mitigation. smart PPE can measure use and remind users to maintain and replace equipment, assuring dependability when required most. By continually monitoring conditions, allowing real-time communication, and enabling data-driven decision-making, this unique technology improves ambulance services and reduces dangers to devoted personnel.

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