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Engineering and technology (PICET), Parul International Conference on

作者： Mohan K. Warbhe Rajendra M. Rewatkar Prateek Verma Yash S. Pachghare Department of Computer Science and Design Faculty of Engineering and Technology Datta Meghe Institute of Higher Education & Research (DU) Sawangi Wardha Maharashtra India Department of Biomedical Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education & Research (DU) Sawangi Wardha Maharashtra India Department of Artificial Intelligence and Machine Learning Faculty of Engineering and Technology Datta Meghe Institute of Higher Education & Research (DU) Sawangi Wardha Maharashtra India

ISBN: (数字)9798350369748

ISBN: (纸本)9798350369755

India is an agriculture based economy and it is one of the most significant sector in India. In traditional agriculture methods, there are various challenges such as reliance on manual labor and limited access to modern farming techniquies due to lack of advanced infrastructure. The spraying of pesticides pose a serious risk to human health as spraying contains potentially hazardous chemicals. This study provides a review on the various techniques being used for spraying pesticides in the agricultural fields. Robots can automate task like planting, weeding and harvesting with better performance in less time. Equipped with sensors and Artificial Intelligence (AI), they can collect the information to make the accurate decisions about soil, crop, health and weather in real time, thereby reducing costs and environmental impact while enhancing productivity. The robotic spraying provides the advantage over traditional methods as it has the ability to maintain its maximum capacity with best efficiency while the pesticide spraying system evenly cover the plants with spray in the appropriate quantities. This connectivity to smart agriculture systems emphasizes the technology's role as a pillar in the shift to efficient and sustainable farming methods. The deployment of these agricultural robots leads to reduction in risk of the potential hazards linked to human contact with dangerous substances and also supports sustainable agriculture.

关键词： Accuracy Reviews Spraying Crops Pesticides Robot sensing systems Agriculture Robots Water resources Farming

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From 5G to 6G: The Role of AI, Machine learning, and Deep learning in Wireless Systems

From 5G to 6G: The Role of AI, Machine Learning, and Deep Le...

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Sentiment Analysis and Deep learning (ICSADL), International Conference on

作者： Pradnyawant M. Gote Praveen Kumar Prateek Verma Prajyot Yesankar Adesh Pawar Saniya Saratkar Department of Computer Science & Design Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research (DU) Wardha Maharashtra India Department of Computer Science & Medical Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research (DU) Wardha Maharashtra India Department of Artificial Intelligence & Machine Learning Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research (DU) Wardha Maharashtra India Department of Artificial Intelligence & Data Science Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research (DU) Wardha Maharashtra India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

The swift progression of wireless communication technologies-specifically from 5G to 6G is an approach that could be the most significant revolutionary leap towards changing connectivity and data transmission forever. Additionally, algorithms of machine learning (ML) and deep learning (DL) in 5G and 6G can offer promising advancements toward predictive maintenance, dynamic spectrum management, and enhanced security. The review of the potentially transformative nature of these technologies underlines the need for future directions of research efforts called for in circumventing challenges towards making full capability exploitation of 6G possible.

关键词： 6G mobile communication Wireless communication Deep learning Tactile Internet Technological innovation Sentiment analysis 5G mobile communication Reviews Heuristic algorithms Security

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Correction to: Utilizing an Emotional Robot Capable of Lip-Syncing in Robot-Assisted Speech Therapy Sessions for Children with Language Disorders

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International Journal of Social Robotics 2023年第2期15卷 185-186页

作者： Esfandbod, Alireza Rokhi, Zeynab Meghdari, Ali F. Taheri, Alireza Alemi, Minoo Karimi, Mahdieh Social and Cognitive Robotics Laboratory Center of Excellence in Design Robotics and Automation (CEDRA) Sharif University of Technology Tehran Iran Fereshtegaan International Branch Islamic Azad University Tehran Iran Department of Humanities Islamic Azad University Tehran Iran Mahan Learning Disorders Center Tehran Iran

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Customer Segmentation Using Clustering Analysis

Customer Segmentation Using Clustering Analysis

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Information technology, Electronics and Intelligent Communication Systems (ICITEICS), IEEE International Conference on

作者： Moses Makuei Jiet Aahash Kamble Chetan Puri Prajyot Yesankar Prateek Verma Rajendra Rewatkar Department of Computer Science & Design Faculty of Engineering and Technology Datta Meghe Institute of Higher Education & Research (DU) Wardha Maharashtra India Department of Artificial Intelligence & Data Science Faculty of Engineering and Technology Datta Meghe Institute of Higher Education & Research (DU) Wardha Maharashtra India Department of Artificial Intelligence & Machine Learning Faculty of Engineering and Technology Datta Meghe Institute of Higher Education & Research (DU) Wardha Maharashtra India Department of Biomedical Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education & Research (DU) Wardha Maharashtra India

ISBN: (数字)9798350382693

ISBN: (纸本)9798350382709

This research focuses on the crucial role of the clustering technique in data mining, specifically in market forecasting and planning. The study presents a comprehensive report on utilizing the k-means clustering technique and data visualization tools to develop a real- time system for a supermarket, predicting sales across various annual cycles. An open-source dataset of a mall with n = 200 customers divided into k = 3 groups, demonstrated high accuracy in predicting day-to-day sales statistics when compared with actual results. The research highlights the effectiveness of the clustering technique in real-time sales prediction for supermarkets.

关键词： Sociology Refining Decision making Data visualization Prediction algorithms Real-time systems Planning

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Hearing it Out: Guiding Robot Sound design through design Thinking

Hearing it Out: Guiding Robot Sound Design through Design Th...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Brian J. Zhang Bastian Orthmann Ilaria Torre Roberto Bresin Jason Fick Iolanda Leite Naomi T. Fitter Collaborative Robotics and Intelligent Systems Institute Oregon State University Corvallis Oregon USA Division of Robotics Perception & Learning KTH Royal Institute of Technology Stockholm Sweden Division of Media Technology & Interaction Design KTH Royal Institute of Technology Stockholm Sweden Music Department Oregon State University Oregon State University Corvallis Oregon USA

Sound can benefit human-robot interaction, but little work has explored questions on the design of nonverbal sound for robots. The unique confluence of sound design and robotics expertise complicates these questions, as most roboticists do not have sound design expertise, necessitating collaborations with sound designers. We sought to understand how roboticists and sound designers approach the problem of robot sound design through two qualitative studies. The first study followed discussions by robotics researchers in focus groups, where these experts described motivations to add robot sound for various purposes. The second study guided music technology students through a generative activity for robot sound design; these sound designers in-training demonstrated high variability in design intent, processes, and inspiration. To unify the two perspectives, we structured recommendations through the design thinking framework, a popular design process. The insights provided in this work may aid roboticists in implementing helpful sounds in their robots, encourage sound designers to enter into collaborations on robot sound, and give key tips and warnings to both.

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Effective Integration of Artificial Intelligence in Medical Education: Practical Tips and Actionable Insights

SSRN

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SSRN 2024年

作者： Garcia, Manuel B. Arif, Yunifa Miftachul Khlaif, Zuheir N. Zhu, Meina de Almeida, Rui Pedro Pereira de Almeida, Raquel Simões Masters, Ken Educational Innovation and Technology Hub FEU Institute of Technology Manila Philippines Universitas Islam Negeri Maulana Malik Ibrahim Malang Indonesia Faculty of Humanities and Educational Sciences An-Najah National University Palestine Palestine Learning Design and Technology Wayne State University United States Center for Studies and Development in Health Universidade do Algarve Portugal Polytechnic University of Porto Portugal Medical Education and Informatics Department

With the increasing popularity of artificial intelligence (AI) applications in medical practices, the integration of AI technologies into medical education has garnered significant attention. However, there exists a noticeable research gap when it comes to providing comprehensive guidelines and recommendations for its successful integration into this domain. Addressing this research gap is crucial as the responsible and effective incorporation of AI in medical education not only ensures that current and future healthcare professionals are well-prepared for the demands of modern medicine but also upholds ethical standards, maximizes the potential benefits of AI, and minimizes potential risks. The objective of this chapter is to fill this gap by offering practical tips and actionable insights for incorporating AI into medical education, encompassing practical, ethical, pedagogical, and professional implications. Consequently, it equips medical educators and learners alike with the knowledge and tools necessary to navigate the evolving landscape of medical education in the age of AI. © 2024, The Authors. All rights reserved.

关键词： Curricula

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Smart Locker 2.0: Leveraging IoT and Machine learning for Secure, User-Friendly Public Storage

Smart Locker 2.0: Leveraging IoT and Machine Learning for Se...

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Artificial Intelligence and Data Engineering (AIDE), International Conference on

作者： Chandrappa S Prithviraj Aditya Pai H Rajesh I S Manjunath Sargur Krishnamurthy R Sneha Shetty R Dept. of Computer Science and Engineering JAIN (Deemed to-be University) Bengaluru India Dept. of Computer Science and Engineering Nitte (Deemed to be University) NMAM Institute of Technology Nitte India Department of CSE MIT Art Design and Technology University Pune India Dept. of AI & ML BMS Institute of Technology and Management Bengaluru India JP Morgan & Chase Co Houston USA Dept. of Artificial Intelligence and Machine Learning Nitte (Deemed to be University) NMAM Institute of Technology Nitte India

ISBN: (数字)9798331527518

ISBN: (纸本)9798331527525

Smart locker systems are a revolutionary technology, combining advanced automation and connectivity to address increasingly demanding requirements for secure, efficient, and convenient storage solutions in numerous scenarios. These intelligent lockers use the latest technologies, such as the Internet of Things (IoT) and mobile applications, to revolutionize the way people store their belongings. Existing Smart Locker System lacks measurable results. To sustain its claims, we include key findings. For security, the system utilizes RFID authentication and biometric security, which reduces unauthorized access by 98% and blocks spoofing attacks. For convenience, a study with 50 users found 92% satisfaction, with 87% preferring it over traditional lockers due to faster access, averaging 3 seconds. For environmental benefits, the system cut power use by using sleep mechanism and saved paper usage by switching to cloud logs. Real-World tests achieved 98% user satisfaction with the university system proving its efficiency, security, and sustainability. This system expounds on multifaceted benefits and functionalities in smart lockers. First, it covers how these lockers provide better security compared to old lock-and-key systems. Using access controls reduces the risk of theft and illegal access to one's valuables and sensitive belongings by a great degree. It has an easy reservation, access, and management of personal lockers via a remote means; this proves to be seamless without needing any physical keys and contactless interactions, ideal for modern spaces considering hygiene and efficiency is top priority. Moreover, it goes on to analyze the flexibility of smart locker systems. From corporate offices to co-working spaces, universities, shopping malls, and public transportation hubs, these lockers cater to diverse user needs, creating flexible and scalable solutions adaptable to a variety of environments.

关键词： Biometrics Cloud computing Switches Machine learning Mobile applications Internet of Things Sustainable development Secure storage Public transportation Radiofrequency identification

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Rethinking Wireless Communication Security in Semantic Internet of Things

arXiv

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arXiv 2022年

作者： Du, Hongyang Wang, Jiacheng Niyato, Dusit Kang, Jiawen Xiong, Zehui Guizani, Mohsen Kim, Dong In The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence Abu Dhabi United Arab Emirates The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Semantic communication is an important participant in the next generation of wireless communications. Enabled by this novel paradigm, the conventional Internet-of-Things (IoT) is evolving toward the semantic IoT (SIoT) to achieve significant system performance improvements. However, traditional wireless communication security techniques for bit transmission cannot be applied directly to the SIoT that focuses on semantic information transmission. One key reason is the lack of new security performance indicators. Thus, we have to rethink the wireless communication security in the SIoT. As such, in the paper, we analyze and compare classical security techniques, i.e., physical layer security, covert communications, and encryption, from the perspective of semantic information security. We highlight the differences among these security techniques when applied to the SIoT. Novel performance indicators such as semantic secrecy outage probability (for physical layer security techniques) and detection error expectation (for covert communication techniques) are proposed. Considering that semantic communications can raise new security issues, we then review attack and defense methods at the semantic level. Finally, we present several promising directions for future secure SIoT research. © 2022, CC BY.

关键词： Semantics

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Data Analytics for Decision Support Systems in Techno-Driven Enterprises

Data Analytics for Decision Support Systems in Techno-Driven...

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Advances in Computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), International Conference on

作者： Rakshitha Priya S Asmita Namjoshi Mahesh Mane Irshadullah Asim Mohammed Rashmitha Shettigar Department of AIML NITTE University (Deemed to Be University) NMAMIT NITTE Udupi Karnataka India SRM Institute of Science and Technology Chennai TamilNadu India Tilak Maharashtra Vidyapeeth Pune India Automotive Design and Development/Engineering Symbiosis School for Online and Digital Learning Pune Maharashtra India FuelCell Energy Inc Syed Ali Chabutra Hyderabad India Department of IT/CS Thakur Ramnarayan college of arts and commerce Mumbai Maharashtra India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

In the digital transformation era the emergence of data analytics plays a significant role in enhanced decision making process in Techno driven Enterprises. The study examines about the impact of data analytics in decision support system to emphasise the role of data analytics on operational tactical and strategical decision making. The big data artificial intelligence and machine learning leverages modern DSS to process large amount of unstructured and structured data optimised performance and extraction of actionable insights in the businesses. The decision support system involves visualisation techniques real time processing of data and predictive analytics that empower the enterprise to make agile and informed decisions. Moreover, the study examines the challenges in security integration and data quality to offer solutions for enhanced and effective decision making. The findings of the study necessitate data driven culture in techno driven enterprises for maintaining competitive edge in the technological landscape.

关键词： Decision support systems Data analysis Data integrity Data visualization Machine learning Market research Real-time systems Security Resource management Predictive analytics

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Pandemic Pivoting: The Use of Home Wi-Fi Accounts and Fast-Food Parking Lots for Teachers’ Internet Connectivity

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Art Education 2023年第3期76卷 32-37页

作者： Harlow, Trina Yang, Yang Ackermann, Sarah Dobberstein, Beth Reeker, Bob Needles, Tim Art Education Department of Art and Design University of Central Arkansas Conway United States Department of Special Education Counseling and Student Affairs College of Education Kansas State University Manhattan United States Executive Director for Teaching Innovation Division of Online and Strategic Learning Ball State University Muncie IN United States University of Wisconsin in Milwaukee United States K–5 Visual Art Specialist & Interventionist Robinson Elementary School Lincoln NE United States Art Teacher/Technology Integration Specialist Smithtown School District in Smithtown New York United States Five Towns College in Dix Hills New York United States University of North Texas Denton United States

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