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ChatGPT-Powered Robot: smart, Interactive Living and Bridging the Future of Education and Entertainment 2

ChatGPT-Powered Robot: Smart, Interactive Living and Bridgin...

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2nd international conference on Sustainable computing and smart Systems (ICSCSS)

作者： Thopate, Kaushalya Gawade, Mayuri Shirbhavikar, Ketaki Kulkami, Mukund Lambor, Shilpa Jaiswal, Krishna Nilesh Vishwakarma Inst Technol Comp Engn Pune Maharashtra India Vishwakarma Inst Technol Artificial Intelligence & Data Sci Pune Maharashtra India Vishwakarma Inst Technol Mech Pune Maharashtra India Vishwakarma Inst Technol Elect & Telecommun Pune Maharashtra India

ISBN: (纸本)9798350391558;9798350379990

Presenting a ground-breaking robotic system that introduces remarkable control mechanisms, encompassing Bluetooth connectivity, voice commands, and gesture inputs. This technological innovation transcends conventional boundaries, characterized by its remarkable capacity to provide precise and intelligent responses to inquiries, a feat attributed to its robust data analytics capabilities harnessed through the integration of ChatGPT. The robot's loudspeaker and microphone facilitate verbal communication, while its range of sensors, including a camera, microphone and accelerometer, enable it to understand its surroundings and interact effectively with users. With ChatGPT and a web API connection for rigorous testing, this robot provides accurate answers on a wide range of topics. Although still in the development stage, it has unlimited potential to become a valuable asset in many fields, including education and entertainment. Future upgrades may include language translation, home automation, and appointment scheduling. Moreover, a major challenge faced by this voice-activated robot is accurately interpreting diverse Indian English accents and dialects in noisy environments, which can lead to misrecognition and reduced interaction effectiveness. Explore this innovative robotic device that can be conveniently operated via Bluetooth, voice commands, and gestures. Its capabilities extend to answering queries through ChatGPT and providing insightful responses by analyzing data. While the robot is still in its development phase, it has the potential to become a valuable asset for entertainment, education and beyond. Other enhancements can be added, such as language translation, home automation, and assistance with scheduling appointments or shopping. The main motive behind this project is to help ungraduated people and to provide entertainment and learning purposes for students who are developing any kind of robot.

关键词： Voice command Assistive Robots Robotics API Key Conversational AI

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Developing smart Precision Farming Using Big data and Cloud-Based intelligent Decision Support System 10

Developing Smart Precision Farming Using Big Data and Cloud-...

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10th international conference on ICT for smart Society, ICISS 2023

作者： Nurcahyo, Aldian Soeparno, Haryono Gaol, Ford Lumban Arifin, Yulyani Bina Nusantara University BINUS Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350339543

This study discusses the development of smart precision farming systems using big data and cloud-based intelligent decision support systems. Big data plays an important role in collecting, storing, and analyzing large amounts of data from various sources related to agriculture, including data from weather stations, soil sensors, satellite imagery, crop yield records, pest and disease reports, and other sources. This study highlights the differences between smart farming and precision farming. This study describes key techniques and system architecture, including data collection, processing, analysis, and decision support components. Utilizing a cloud platform enables scalability and optimized performance, which lowers costs and makes it safer and easier to manage. The integration of big data and Alibaba cloud computing in smart precision farming can improve farming productivity by providing timely information and recommendations to farmers for better decision-making. Finally, the system produces smart precision farming, which provides cost-effective real-Time monitoring and predictive analytics to increase agricultural production and sustainability. © 2023 IEEE.

关键词： Decision support systems

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A Derived Framework for Immersive analytics: Use Cases in smart City and Pokémon Interactive data Visualization

A Derived Framework for Immersive Analytics: Use Cases in Sm...

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2024 IEEE international conference on computing, ICOCO 2024

作者： Jamaludin, Najwa Ayuni Binti Mohamed, Farhan Bin Siang, Chan Vei Heng, Lee Jun Sunar, Mohd Shahrizal Bin Faculty of Computing Universiti Teknologi Malaysia Johor Johor Bahru Malaysia Media and Game Innovation Centre of Excellence Faculty of Computing Universiti Teknologi Malaysia Johor Johor Bahru Malaysia Institute of Human Centered Engineering Faculty of Computing Universiti Teknologi Malaysia Johor Johor Bahru Malaysia

ISBN: (纸本)9798331530303

Immersive analytics (IA) explores the use of immersive technologies to enhance data visualization and interaction. To maximize the potential of IA, it is essential to develop effective and practical applications. In this context, an IA design framework plays a crucial role as it provides a structured approach to define user requirements and guide the development of the application. This paper proposed a design framework for IA, adapted from several established works. The framework was applied to two use cases: visualizing smart city data in a virtual reality environment and Pokémon data in a mixed reality environment. These use cases demonstrate the applicability of the framework in guiding the development of IA applications that can be used to perform various tasks in different immersive settings and domains. Besides, a user study was conducted with 30 participants to assess their perceived workload while interacting with these applications. Future work will focus on conducting more comprehensive evaluations in terms effectiveness and efficiency to provide insights for further enhancements. ©2024 IEEE.

关键词： Virtual environments

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Facial Video analytics: An intelligent Approach to Heart Rate Estimation Using AI Framework 6

Facial Video Analytics: An Intelligent Approach to Heart Rat...

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6th IEEE international conference on Emerging smart computing and Informatics, ESCI 2024

作者： Toley, Minal C. Mishra, Raj Gaurav Shirsath, Vishal School of Engineering ADYPU Lohegaon Pune India

ISBN: (纸本)9798350306613

The development of remote sensing of vital signs, which use a camera instead of a skin-contact sensor, has improved the measurement environment. Two ideas form the foundation of the camera-based approach: colour and motion. Remote ballistocardiography (RBCG), a motion-based technique, examines the minute movements of the head caused by heartbeat, whereas remote photoplethysmography (RPPG), a color-based technique, measures the colour variation of the face caused by blood reflection. Accurate heart rate monitoring is vital to collecting valuable physical data from human participants. Because of its ease of use and affordability, face video-based heart rate estimate has gained a lot of attention lately. Its precision, dependability, and computing complexity, however, still fall short of expectations. Our goal in this work has been to create a novel deep learning system that use RGB camera to estimate heart rates in real time. The aim of this research topic is to generating an AI algorithm for Heart Rate monitoring from facial video data and integrate it into a real-time heart rate monitoring system. The system will be designed to be user-friendly and easily deployable in various settings such as hospitals, clinics, and homes. © 2024 IEEE.

关键词： Artificial Intelligence Heart Rate Heart Rate Estimation Non-contact Remote PPG

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Multi-layered Architecture to Monitor and Control the Energy Management in smart Cities

Multi-layered Architecture to Monitor and Control the Energy...

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international conference on data analytics, intelligent computing, and Cyber Security, ICDIC 2020

作者： Damodaram, A.K. Sreenivasa Chakravarthi, S. Venkateswara Reddy, L. Reddy Madhavi, K. AP Tirupati India AP Tirupati India Department of CSE KG Reddy College of Engineering AP Hyderabad India

ISBN: (纸本)9789811941610

Energy meter monitoring and control management in real time still have several limitations in smart city establishments. One of the essential components of smart city is energy meter monitoring and control in real time. Since it is a herculean task for the energy companies to monitor and control energy meter in collecting the data on energy consumption, billing, payments and other managerial aspects in smart city environment, a suitable wireless sensor network architecture that encompasses emerging technologies like smart devices, Cloud–Fog computing, IoT and drones may be an approach to provide a solution in this regard. Present day communication technologies revolutionized the way smart phones and smart gadgets/devices are deployed to access, acquire, store and share data. Internet of Things (IoT), in the recent past, facilities to provide several applications and solutions in making our lives ‘smart’ leading to ‘smart city’ establishments. The present article proposes a novel ‘three-layered’ wireless sensor network architecture for energy meter monitoring control management in real time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Wearable smart Health Monitoring Transmitter and Portable Receiver Systems for Enhanced Wellness Insights 2

Wearable Smart Health Monitoring Transmitter and Portable Re...

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2nd international conference on Automation, computing and Renewable Systems, ICACRS 2023

作者： Sivaprasad, T.C. Surendhar, R. Heiner, A.J. Electronics and Communication Engineering Saveetha Engineering College Chennai India

ISBN: (纸本)9798350340235

This study presents the development and evaluation of a smart wearable belt designed for comprehensive health monitoring and fall detection. The wearable integrates advanced sensors, including vibration and heartbeat, to give users real-time insights into their well-being. The vibration sensor, meticulously calibrated for precise fall detection, exhibited high sensitivity and responsiveness, distinguishing between daily activities and potential accidents. Simultaneously, the heartbeat sensor demonstrated accurate and consistent heart rate monitoring, contributing to proactive cardiovascular health management. The seamless integration of these sensors, supported by MQTT connectivity and secure data transmission, ensures a user-friendly experience. Cloud integration enhances data processing and analytics, empowering users with a comprehensive health dashboard. Results indicate the reliability of the fall detection system and the accuracy of heart rate monitoring. This intelligent wearable belt represents a promising advancement in health technology, offering a holistic solution for users seeking real-time health insights and proactive fall prevention. Ongoing research focuses on refining algorithms and incorporating user feedback for continuous improvement and broader applications in personalizedhealth care. © 2023 IEEE.

关键词： data analytics Patient monitoring smart belt Wearable Sensor

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analytics of Retail Store Consumption Using Physical computing 7th

Analytics of Retail Store Consumption Using Physical Computi...

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7th international conference on Information and Communication Technology for intelligent Systems, ICTIS 2023

作者： Bang, Arti Bansode, Chandramani Talware, Rajendra Kshirsagar, Ketki Purandare, Radhika Ratnaparkhi, Archana Deshmukh, Minal Department of Electronics and Telecommunication Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9789819937608

Visibility and Presentation of goods for ease of buying and greater customer experience is always a matter of great concern for supermarkets and malls. smart Retail Rack analytics, a proposed system that targets improving the customer experience for boosting the sale of goods in supermarkets, is an embedded system. It collects data from surrounding racks in the retail stores using physical computing devices and software systems, further used for analytics and to generate parametric reports for the usage by managers to evaluate and optimize the store plan. Sensors, and Bluetooth low energy, are deployed for collecting data. Then ESP-32 microcontroller processes this collected data, and transfers it to Raspberry pi to upload to the cloud. The system enables information like person detection, people counting, customer heat map section-wise, and average time spent by customers in a particular section. smart Retail Rack analytics easily overcomes day-to-day difficulties faced by retailers and improves customer experience resulting in better management of stores. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Microcontrollers

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A Practical and Privacy-Preserving Vehicular data Sharing Framework by Using Blockchain 22

A Practical and Privacy-Preserving Vehicular Data Sharing Fr...

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IEEE 22nd international conference on Trust, Security and Privacy in computing and Communications (TrustCom) / BigdataSE conference / CSE conference / EUC conference / ISCI conference

作者： Yang, Xu Wang, Ao Wang, Qiuhao Qi, Saiyu Qi, Yong Xi An Jiao Tong Univ Sch Comp Sci & Technol Xian 710049 Peoples R China

ISBN: (纸本)9798350381993;9798350382006

As the integration of the Internet of Vehicles and social networks, vehicular social networks (VSNs) are promising to boost the realization of intelligent transportation system. Recently, vehicular data privacy has been paid increasing attention in data sharing. Searchable encryption as a promising cryptographic primitive can be utilized to ensure vehicular data confidentiality without sacrificing data searchability. However, most vehicular data sharing schemes rely on centralized cloud servers, which are vulnerable to the single point of failure and distributed denial of service (DDoS) attacks. In this paper, we propose VehShare, a decentralized framework for privacy-preserving vehicular data sharing. We resort to the smart contract to implement a trusted platform for vehicles to share their encrypted vehicular data. To provide efficient access control, we design an authorization-based on-chain access control scheme with a lightweight cryptographic primitive. Moreover, we design a time synchronization-based non-interactive search token generation scheme to achieve efficient privacy-preserving search queries, while satisfying forward and backward security. We formally analyze the security of VehShare and extensive experiments demonstrate the efficiency of VehShare.

关键词： vehicular social network vehicular data sharing symmetric searchable encryption keyword search blockchain

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IoT-Driven Agricultural Monitoring Architecture with Novel Light Machine Learning for Enhanced Precision Crop Health Analysis 3rd

IoT-Driven Agricultural Monitoring Architecture with Novel L...

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3rd international conference on intelligent Systems and Sustainable computing, ICISSC 2023

作者： Andi, Hari Krishnan Ramasamy, Lokeshkumar Nramban Kannan, Senthil Kumar Murugesan, Sasikumar Benarji, Bejjam S. N. Manogaran, Umamaheswari Sengan, Sudhakar Centre for Postgraduate Studies Asia Metropolitan University Johor81750 Malaysia School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Computer Science and Engineering Deemed to Be University Vel Tech Rangarajan Dr Sagunthala R&H12D Institute of Science and Technology Tamil Nadu Chennai600062 India C. Abdul Hakeem College of Engineering & Technology Tamil Nadu Melvisharam Ranipet632509 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522502 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli627451 India

ISBN: (纸本)9789819783540

In the age of digital transformation, agriculture is harnessing the potential of advanced technologies to address global challenges related to food security and environmental sustainability. While smart Agriculture and Precision Agriculture lay the foundation, there remains a pressing need for real-time, granular data processing to realize their full potential. Edge computing, coupled with Machine Intelligence (MI), promises a solution, yet existing models often lack the adaptability and real-time efficiency demanded by diverse agricultural scenarios. Addressing these challenges, this paper proposes the Precision Intensive Crop Health Observer (PICHO). PICHO is an innovative three-tier architecture comprising the Field data Interface Unit (FDIU) for seamless sensor data collection, the Edge analytics Processor (EAP) for real-time edge-based analytics, and the Cloud Coordination Hub (CCH) for data storage and in-depth analysis. Central to the EAP's efficacy is the lightweight learning model LENet, which is designed with dual pipelines for processing sensor and image data. Specifically crafted to be trained on resource-constrained edge devices, LENet ensures that PICHO remains adaptable, efficient, and poised to redefine the future of precision agriculture. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： smart agriculture

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smart Contract Vulnerability Detection Based on Multi Graph Convolutional Neural Networks with Self-attention 20th

Smart Contract Vulnerability Detection Based on Multi Graph ...

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20th international conference on intelligent computing (ICIC)

作者： Li, Jiale Yu, Xiao Yu, Jie Sun, Haoxin Sun, Mengdi Shandong Univ Technol Sch Comp Sci & Technol Zibo 255049 Shandong Peoples R China

ISBN: (纸本)9789819755875;9789819755882

smart contracts can contain vulnerable program code, making their security a significant concern in the past few years. Traditional detection techniques rely on expert defined features and source code analysis, but both have scalability issues and high false alarm rates. This paper presents a method for the detection of vulnerabilities in smart contracts, employing a multi graph convolutional neural network and self-attention mechanism. The method models the key function information, flow of control, and flow of data information of the smart contract source code as a semantic graph to emphasize the relationship between the flow of data and the flow of control in program operation. It predicts learning edges between nodes in the graph using an edge prediction network and constructs a multi graph of the smart contract semantics. Additionally, it utilizes a self-attention mechanism to gather and extract features from many layers to achieve precise detection of smart contract vulnerabilities. Outcomes of an experiment demonstrate that the proposed vulnerability detection method has significant advantages in identifying reentrant vulnerabilities and timestamp dependency vulnerabilities, with accuracy rates of 92.5% and 92.67%.

关键词： Blockchain smart Contracts Vulnerability Detection Graph Neural Networks Self-Attention

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