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Hive Destruction Protocol: An Automated Defense System Utilizing YOLO Human Recognition and Real-Time GPS Tracking 3

Hive Destruction Protocol: An Automated Defense System Utili...

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3rd international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Vyshak, T.M. Gaayana, G.R. Sarala, T. Dept. of Electronics and Communication Engineering Bnm Institute of Technology Affiliated to Vtu Bengaluru India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515911

The Hive Destruction Protocol (HDP) introduces a cutting-edge automated border defense system that enhances security operations through advanced human recognition using YOLO, precise GPS tracking, and coordinated drone responses. Soldiers are equipped with camera-integrated spectacles that facilitate the rapid identification of enemy targets via visual cues and hand gestures. Upon confirming a target, the system transmits accurate GPS coordinates in real time to autonomous drones, which are deployed to neutralize threats from multiple angles, creating confusion and minimizing detection risk. To ensure reliability and real-time processing in dynamic environments, HDP employs optimized communication protocols for secure data exchange between ground personnel and drones, allowing for seamless coordination among multiple units, each capable of independently engaging identified threats based on shared GPS data. The integration of machine learning algorithms improves the system even more flexible to changing field conditions, improving detection accuracy and robustness under various environmental constraints. Overall, the Hive Destruction Protocol represents a forward-thinking solution for border defense, leveraging artificial intelligence and automation to provide proactive and responsive capabilities in critical security applications. © 2025 IEEE.

关键词： Target drones

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Secure Image Communication: Integrating Diffie-Hellman Key Exchange for Enhanced Confidentiality 3

Secure Image Communication: Integrating Diffie-Hellman Key E...

引用

3rd international conference on Artificial intelligence For Internet of Things, AIIoT 2024

作者： Shifani Francis, M. Dhalia Sweetlin, J. Sandhiya, M. Madras Institute of Technology Department of Information Technology Chennai India

ISBN: (纸本)9798350372120

The safety of data or images is a critical step in the vast field of Internet of Things (IoT) network communication. Image encryption is a well-known technique for protecting the information contained in images in order to maintain their confidentiality, authenticity, and integrity. The goal of the secure communication system described in the work proposed is to make image data exchange easier while preserving confidentiality and integrity. To create a secret key that is shared between communicating parties over an unsecure channel, the system uses the Diffie-Hellman key exchange mechanism. Sensitive image information connected to the sent photos is encrypted and decrypted using this shared key. In order to prevent eavesdropping and unauthorized access, the Diffie-Hellman key exchange algorithm makes it possible to securely generate a shared key without the need for direct key transmission. Encrypted image data guarantees that the sensitive information contained in the images can only be accessed and decoded by the designated recipient, who has the necessary decryption key. Through the integration of image data encryption techniques with the Diffie-Hellman key exchange's strength, the proposed system aims to offer a dependable and secure means of transferring images while protecting the privacy and confidentiality of related sensitive data. This system's efficiency stems from its capacity to securely exchange images over possibly unreliable channels while preserving the data's integrity and confidentiality. This system's efficiency extends beyond secure image exchange, finding potential applications in signal and image processing and enhancing its versatility for broader usage over possibly unreliable channels while preserving data integrity and confidentiality. © 2024 IEEE.

关键词： Electronic data interchange

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Advanced Camouflage robot for Military Spying applications using Sensor Fusion and Machine Learning 3

Advanced Camouflage Robot for Military Spying Applications u...

引用

3rd IEEE international conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Kulkarni, Neeraj P Khan, Subim N. Rathod, Rahul Ramkishan Choure, Ajay Raosaheb Chinchole, Mahesh Gokul Jspm Rajarshi Shahu College of Engineering Tathawade Pune India Soet D Y Patil University Ambi Pune India Bhivarabai Sawant Institute Of Technology And Research E&tc Department Wagholi Pune India Nutan Maharashtra Institute of Engineering and Technology E&tc Department Pune India

ISBN: (纸本)9798350354348

The current defense application scenario. the ability to blend into the environment is crucial for reducing detection and enhancing operational efficiency. This paper presents the development of an advanced camouflage robot to dynamically adapt its color to match its surroundings. The proposed system utilizes a combination of machine learning, computer vision, and sensor fusion to achieve camouflaging using the RGB LED panels mounted on the robot to adapt to the color of the surroundings. The robot is equipped with a video camera system that captures real-time video feed of the environment. The captured video is then processed by a trained machine learning model, which analyzes the color distribution in the surroundings. Simultaneously, the robot uses RGB color sensors to accurately detect the colors present in its immediate vicinity. The data from both the camera and the sensors are integrated to determine the predominant color around the robot. The hybrid camouflaging approach involves feeding the combined data into the machine learning model, which then calculates the color of maximum distribution. The robot then activates its RGB panels, adjusting their color to blend with the identified predominant color in the environment thereby making it difficult to locate. This process allows the robot to effectively camouflage itself, minimizing its visual footprint. KNN and sensor fusion techniques are used to achieve this task. © 2024 IEEE.

关键词： Nearest neighbor search

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Analysis of Various Image Segmentation Techniques on Retinal OCT Images 3

Analysis of Various Image Segmentation Techniques on Retinal...

引用

3rd international conference on Artificial intelligence and Smart Energy, ICAIS 2023

作者： Sheeba, T.M. Albert Antony Raj, S. Anand, M. Srm Institute of Science and Technology College of Science and Humanities Department of Computer Applications Chennai India Srm Institute of Science and Technology College of Engineering and Technology Department of Networking and Communications Chennai India

ISBN: (纸本)9781665462167

Image segmentation is one of the most important processes involved in image processing. Segmenting an image is breaking it up into smaller pieces, or segments. These are the areas where it is most helpful because processing the complete image would be inefficient for tasks like object recognition or image compression. Image segmentation is the process of dividing an image's elements for further processing. This article looked at a number of image segmentation techniques, including the threshold approach, edge-based method, and clustering-based method. The segmentation method that is most effective for separating images in OCT images is clustering-based segmentation. To reduce the speckle noise during preprocessing, the wiener filter approach is used. With regards to the threshold, edge-based (Sobel, Canny, Robert's), and clustering-based segmentation techniques, calculate MSE (mean square error) and PSNR (peak signal to noise ratio) values for the segmented image quality. © 2023 IEEE.

关键词： Image segmentation

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Artificial intelligence of Patients Management for Injured Patient and robotic assisted Physiotherapy Rehabilitation 3

Artificial Intelligence of Patients Management for Injured P...

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3rd international conference for Innovation in technology, INOCON 2024

作者： Padmaavathy, P.A. Thilagavathi, J. Selvi, K. Ramachandran, G. Kumar, G. Suresh Reddy, D.V. Lokeswar Justin, B.V. Febiyola Karpagam Academy of Higher Education Department of Management Coimbatore India Arjun College of Technology Department of Ai & Ds Coimbatore India Department of Management Studies Chennai77 India Ece Vinayaka Mission's Kirupananda Variyar Engineering College Salem India Andhra Pradesh Pulivendula516390 India St. Peter's Institute of Higher Education and Research Department of Biochemistry Avadi Chennai600054 India

ISBN: (纸本)9798350381931

It has been observed that technology has shown to be extremely helpful in the healthcare industry. Numerous apps that facilitate patient and physician lives are being developed. Artificial intelligence, machine learning, and virtual reality are among the most widely used technology in therapeutic applications. With the help of apps like this medical technology, health professionals are acquiring the tools they need to give patients in need the kind of care and assistance they need. Additionally, it lessens the burdens of clinicians and provides the ability to manage more customers than before. As injury care, physical strength, body functionality, and total body activity have improved in recent decades along with engagement in body movement research as opposed to drug use and surgery the necessity for physical therapy has increased. Along with the necessity for rehab centers and physiotherapists, the surge in physical activity has increased the requirement for physiotherapy. Physiotherapists now have a helpful workload aid in the form of medical technology. Smart workouts are dependable and inspiring activities that lower the risk of injury and strengthen the muscle-bone system. Unconscious movements have the potential to injure a person's body or impede the growth of exercise. The goal of this study is to examine both orthopedic patients and athletes. The primary focus is performing the exercise correctly according to the specified plan within the constraints of the individual, thanks to the designed algorithm and equipment. The system notifies a user when they complete the necessary movement to the desired degree while wearing an elbow or knee brace, depending on the intended application and the program designed by a doctor or trainer. © 2024 IEEE.

关键词： robotics

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Smart AgroAid: AI-Driven Web-based Crop Disease Detection and Management System 3

Smart AgroAid: AI-Driven Web-based Crop Disease Detection an...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Dighe, Suyog Balu Kotkar, Akshay Nandu Modhave, Shravani Dattatraya Patekar, Tushar Sudhakar Jawale, M.A. Sanjivani College of Engineering Department of Information Technology Kopargaon India

ISBN: (纸本)9798331509675

Crop diseases pose a serious danger to global food security and cause large financial losses in the agricultural sector. In order to provide accurate diagnosis and treatment, this study introduces a web-based crop disease detection system that integrates environmental data and sophisticated picture processing. The system analyzes leaf pictures and uses convolutional neural networks (CNNs) to classify plant illnesses. To improve diagnostic precision, environmental elements including soil characteristics, temperature, and humidity are also taken into account. Farmers input leaf photos using the system's user-friendly web interface, and they will receive personalized treatment recommendations along with real-time disease diagnosis findings. This system's sturdy design guarantees scalability and accessibility, especially in rural and resource-constrained locations, and is inspired by earlier research combining ML and AI for agricultural applications. This approach aims to boost output, reduce crop losses, and promote sustainable agricultural practices by providing useful insights and automating disease detection. The multilingual solution ensures inclusion for varied farming communities by automating disease identification and offering actionable insights. © 2025 IEEE.

关键词： Artificial intelligence Crop Disease Detection Environmental Data Integration Machine Learning Multilingual Support Sustainable Farming Web-Based System

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A Study on Working and applications of Sequential Deep Learning Models 3

A Study on Working and Applications of Sequential Deep Learn...

引用

3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Swathi, S.B. Juluri, SaiNikhil Komarali, Pooja Madhukar Kandhagatla, Akshaya Chavan, Soumya Information Technology Kakatiya Institute of Technology and Science Warangal India

ISBN: (纸本)9798350322842

This research study intends to explore the field of sequence-to-sequence and language models. To determine how this research helped towards the new era of artificial general intelligence. RNN, Bi-RNN, LSTM, Bi-LSTM, Encoder and Decoder, Bert, Attention Models, GPT, GPT-2, GPT -3, GPT -4 are some of the sequence models and transformers that are utilized in performing various natural language processing tasks like text summarization, named entity recognition, chatbots, question answering. The essential factor of sequence models is that the data processing is not more evenly and independently widely dispersed samples;rather, the data have some degree of dependence since they are processed in a sequential manner. Mainly this models deals with the text data as input. The applicability of sequential models in many domains will be discussed. © 2023 IEEE.

关键词： Natural language processing systems

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A multi-objective optimization model of robot path planning under different scenarios 3

A multi-objective optimization model of robot path planning ...

引用

3rd IEEE international conference on Power, Electronics and Computer applications, ICPECA 2023

作者： Ren, Hourui Shi, Yuanlin Qiao, Yuting Chengdu University of Technology Chengdu China

ISBN: (纸本)9781665472784

With the rapid development of logistics industry, path planning of mobile robots has been widely concerned. The main purpose of this paper is to solve the problem of path planning for autonomous mobile robots in static environment. The problem can be solved by determining a collision-free path that satisfies the selected criteria of shortest distance and path smoothness. The proposed multi-objective path planning model aims at scientific and reasonable path planning for mobile robots to increase the path smoothness and reduce the moving distance. Firstly, according to the characteristics of obstacles, two groups of different robot workspace scenarios were set from the degree and density of obstacles. Secondly, a multi-objective nonlinear programming model is established to maximize path smoothness and minimize path distance. Finally, different scenarios are simulated, and a fast non-dominated sorting genetic algorithm based on elite strategy (NSGAII) is used to solve the model. Simulation results show that the multi-objective path planning model established in this paper can generate an optimal feasible path even in a complex environment, so as to overcome the shortcomings of traditional methods such as grid method. Moreover, compared with recent path planning techniques, the proposed multi-objective evolutionary algorithm is highly competitive in path optimization. © 2023 IEEE.

关键词： Mobile robots

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Adaptive Terminal Sliding Mode Control Using RBF Neural Network for Industrial robot Manipulators 3rd

Adaptive Terminal Sliding Mode Control Using RBF Neural Netw...

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3rd international conference on Advances in Information and Communication technology, ICTA 2024

作者： Van Chuong, Le Phuong, Ho Sy Tu, Duong Dinh Van Du, Phan Son, Dang Thai Anh, Mai The Van Nam, Dinh Cuong, Ta Hung Van Vy, Phan Vinh University Nghe An Vinh City Viet Nam

ISBN: (纸本)9783031809422

This paper presents an adaptive terminal sliding mode control method for industrial robot manipulators. The proposed approach ensures finite-time error convergence without requiring prior knowledge of the bounds of uncertainties and external disturbances. This is accomplished by employing an RBF neural network and an adaptive control algorithm to estimate the upper limits of these uncertainties. Additionally, the controller eliminates chattering effects while maintaining robustness and accuracy. The stability of the control algorithm is rigorously validated using Lyapunov theory. The proposed controller has been tested through simulations on a three-degree-of-freedom robot to demonstrate its effectiveness. The simulation results confirm the controller's ability to handle uncertainties and disturbances effectively, highlighting its potential for real-world industrial applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adaptive control systems

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Design and Development of an Underwater robot Inspired by Sea Turtles 21

Design and Development of an Underwater Robot Inspired by Se...

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21st IEEE international conference on Mechatronics and Automation (IEEE ICMA)

作者： Li, Xiang He, Wei Li, Jinfeng Xia, Dan Luo, Xiang Shi, Yunde Ji, Xiaoqiang Yang, Yuan Southeast Univ Sch Mech Engn Nanjing Peoples R China Chinese Univ Hongkong Shenzhen Inst Artificial Intelligence & Robot Soc Shenzhen Peoples R China Southeast Univ Sch Instrument Sci & Engn Nanjing Peoples R China

ISBN: (纸本)9798350388084;9798350388077

In this paper, we design and build a bionic robot based on a sea turtle. The part of the device includes joint design, sealing design and controls. The sinusoidal curve is used to analyze the turtle robot's fin motion profile and to control the way it moves. Individual joints are given movement curves during sea turtle movement. Synergy of different fin joints during sea turtle movement is verified with MATLAB software. In addition, we also measure the propulsion force of the bionic turtle robot. The experimental results show that the use of trigonometric curves for the fin joint trajectory of the turtle robot can lead to an appropriate motion.

关键词： bionic sea turtle robot joint control sinusoidal curve MATLAB

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