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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Gupta, Priyanka Revathi, V. Hameed, Ali Abduhussien Gupta, Manish Yadav, Suman Avdhesh Rao, Bolleddu Devananda Institute of Aeronautical Engineering Department of Computer Science and Engineering Telangana Hyderabad India New Horizon College of Engineering Department of Applied Sciences Bangalore India The Islamic University College of Medical Technology Radiology Techniques Department Najaf Iraq Lovely Professional University Phagwara India Iilm University Department of Computer Science & Engineering Uttar Pradesh Greater Noida India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798350350067

Energy-efficient design and operation are essential for next-generation sensor networks to persist and require less maintenance. This paper describes a novel energy-efficient sensor network. It uses superior data routing and aggregation. Three novel algorithms-EARA, DFAA, and Adaptive Data Sampling-make this strategy practicable. EARA sends data with little energy, DFAA collects all data to eliminate duplicates, and ADSA adjusts sample rates based on relevance and variability. Each piece of software sends, manages, and changes sample rates with minimal energy. This innovative energy-saving strategy is tested against static-duty cycling, non-adaptive data aggregation, fixed-rate data sampling, high-energy data transmission, centralized data routing, and unoptimized sensor node location. The recommended solution outperforms network lifetime, energy usage, data accuracy, latency, scalability, and dependability. Energy savings, ease of use, affordability, adaptability, long-lastingness, and network lifespan are usually better with the proposed response. Scatter plots illustrate how much better the proposed method saves energy and works properly. The EARA, DFAA, and ADSA algorithm-based techniques offer great potential for energy-efficient sensor networks. This strategy stabilizes and prolongs sensor network configurations by optimizing data pathways, aggregating data, and adaptively sampling data. The results show that it works, making it a novel strategy for the future generation of sensor networks that demand higher performance and less energy. © 2024 IEEE.

关键词： Adaptive Data Sampling Data Aggregation Data Management Energy Consumption Energy Efficiency Energy-Aware Routing Network Lifetime Performance Evaluation Sensor Networks Sustainability

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A Novel Hybrid Architecture for Superior IoT Threat Detection through Real IoT Environments

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computers, Materials & Continua 2024年第11期81卷 2299-2316页

作者： Bassam Mohammad Elzaghmouri Yosef Hasan Fayez Jbara Said Elaiwat Nisreen Innab Ahmed Abdelgader Fadol Osman Mohammed Awad Mohammed Ataelfadiel Farah H.Zawaideh Mouiad Fadeil Alawneh Asef Al-Khateeb Marwan Abu-Zanona Department of Computer Science Faculty of Computer Science and Information TechnologyJerash UniversityJerash26150Jordan Computer Engineering Department College of Engineering&Information Technology Buraydah CollegesBuraydah51418Saudi Arabia Faculty of Architecture and Design Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityDiriyahRiyadh13713Saudi Arabia Applied College King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Business Intelligence and Data Analysis Faculty of Financial Sciences and BusinessIrbid National UniversityIrbid21110Jordan Faculty of Information Technology Ajloun National UniversityAjlun26810Jordan Department of Management Information Systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia

As the Internet of Things(IoT)continues to expand,incorporating a vast array of devices into a digital ecosystem also increases the risk of cyber threats,necessitating robust defense *** paper presents an innovative hybrid deep learning architecture that excels at detecting IoT threats in real-world *** proposed model combines Convolutional Neural Networks(CNN),Bidirectional Long Short-Term Memory(BLSTM),Gated Recurrent Units(GRU),and Attention mechanisms into a cohesive *** integrated structure aims to enhance the detection and classification of complex cyber threats while accommodating the operational constraints of diverse IoT *** evaluated our model using the RT-IoT2022 dataset,which includes various devices,standard operations,and simulated *** research’s significance lies in the comprehensive evaluation metrics,including Cohen Kappa and Matthews Correlation Coefficient(MCC),which underscore the model’s reliability and predictive *** model surpassed traditional machine learning algorithms and the state-of-the-art,achieving over 99.6%precision,recall,F1-score,False Positive Rate(FPR),Detection Time,and accuracy,effectively identifying specific threats such as Message Queuing Telemetry Transport(MQTT)Publish,Denial of Service Synchronize network packet crafting tool(DOS SYN Hping),and Network Mapper Operating System Detection(NMAP OS DETECTION).The experimental analysis reveals a significant improvement over existing detection systems,significantly enhancing IoT security *** our experimental analysis,we have demonstrated a remarkable enhancement in comparison to existing detection systems,which significantly strength-ens the security standards of *** model effectively addresses the need for advanced,dependable,and adaptable security solutions,serving as a symbol of the power of deep learning in strengthening IoT ecosystems amidst the constantly evolving cyber threat *** achievemen

关键词： A hybrid deep learning model IoT threat detection real IoT environments cybersecurity attention mechanism

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The UNICT-TEAM Vision Modules for the Mohamed Bin Zayed International Robotics Challenge 2020 7th

The UNICT-TEAM Vision Modules for the Mohamed Bin Zayed Inte...

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7th International Conference on computer Vision and Image Processing, CVIP 2022

作者： Battiato, Sebastiano Cantelli, Luciano D’Urso, Fabio Farinella, Giovanni Maria Guarnera, Luca Guastella, Dario Calogero Leonardi, Rosario Noce, Alessia Li Muscato, Giovanni Piazza, Alessio Ragusa, Francesco Santoro, Corrado Sutera, Giuseppe Zappala, Antonio Department of Math and Computer Science University of Catania Catania Italy Department of Electrical Electronic and Computer Engineering University of Catania Catania Italy

ISBN: (纸本)9783031314063

Real-world advanced robotics applications cannot be con¬ceived without the employment of onboard visual perception. By per¬ception we refer not only to image acquisition, but more importantly to the information extraction required to carry out the robotic task. In this paper the computer vision system developed by the team of the Uni¬versity of Catania for the Mohamed Bin Zayed International Robotics Challenge 2020 is presented. The two challenges required to: 1) develop a team of drones for grasping a ball attached to another flying vehi¬cle and to pierce a set of randomly placed balloons, 2) to build a wall by adopting a mobile manipulator and a flying vehicle. Several aspects have been taken into account in order to obtain a real-time and robust system, which are crucial features in demanding situations such as the ones posed by the challenges. The experimental results achieved in the real-world setting are reported. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Object recognition

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Examining Various Search Algorithms in AI with Appropriate Literature and Their Performances Against a Human Agent in the Snake Game 14

Examining Various Search Algorithms in AI with Appropriate L...

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14th IEEE Global engineering Education Conference, EDUCON 2023

作者： Mim, Sheikh Sharfuddin Islam, Md Nahin Logofatu, Doina Frankfurt University of Applied Sciences Department of Computer Science and Engineering Frankfurt am Main Germany

ISBN: (纸本)9798350399431

Artificial intelligence (AI) is one of computer science's most crucial subfields. AI applications are growing rapidly. Games are the main place where artificial intelligence is actually used. AI is used to create the game's non-player characters, also referred to as NPCs. Although there are a lot of alternative ways to implement AI in a game, the search strategy is by far the most common. A variety of different search algorithms can be used to construct AI in video games. This paper's main objective is to use the snake game as a comparative tool to examine the differences between search algorithms employed by human agents and those used in AI. This paper presents detailed assessments of informed and uninformed search strategies as well as experiments on Hamiltonian search. This paper also addresses a few widely used techniques, like finite state machines, behavior trees, tree search, etc., frequently used while creating AI. We get to the conclusion that some algorithms are better candidates for use as search algorithms based on the results of thorough expla-nations and trials. We found that the Human Agent performs poorly when compared to the Depth-First Search, Breadth-First Search, Hamiltonian Search, and Best-First Search algorithms, while the A ∗ Search algorithm surpasses them all significantly. © 2023 IEEE.

关键词： Artificial intelligence

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Flutter Based Mobile Application for Electric Vehicle Charging Reservation 8

Flutter Based Mobile Application for Electric Vehicle Chargi...

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8th IEEE International Conference for Convergence in Technology, I2CT 2023

作者： Hari Krishna, S.M. Geethanjali, R. Naik, Dhanya Maruti Hemashree, N. Bhabya, Bhabya M S Ramaiah University of Applied Sciences Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350334012

The growing number of Electric Vehicles (EV) in the transportation sector has brought with it challenges associated with charging of the vehicle at the charging stations, like clustering of vehicles at a particular station, leading to longer waiting hours due to low number of charging outlets available. This has led to loss in time and energy of the EV owners and a frustrating experience in locating a nearby charging station. The paper entrails a solution to tackle these issues, by proposing a mobile application to pre book or reserve a charging port ahead of time at any available charging station for charging the EV, thus ensuring effective service to the users, reducing the clustering of vehicles at the charging stations and thereby less waiting time. The proposed system provides the user with details such as the location of a charging station, number and type of chargers present at a charging station and availability of slots during a specific period. It also allows users to book an available slot with a secured payment gateway and maintains user feedback. © 2023 IEEE.

关键词： Mobile computing

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Closest Celestial Body Search Using KD Trees

Closest Celestial Body Search Using KD Trees

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Priya Ponnusamy, P. Shabariram, C.P. Umayal, V.R. Susmeta, A. PSG Institute of Technology and Applied Research Neelambur Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350348217

A Binary Search Tree is expanded into a KD Tree to handle the multi-dimensional key searches. A discriminator makes the KD tree different from the BST. This discriminator will take branching decisions at every level based on the key search. It can handle multi-dimensional coordinate object searching. K-d trees enable O(klogn) lookup times for the k nearest points to some point x. This is extremely useful, especially in cases where an O(n) lookup time is intractable already. In this work, a kd tree has been created based on how a celestial body is positioned in relation to the sun. It aims at finding the minimum in a particular dimension, searching for a celestial body and its nearest neighbor. © 2023 IEEE.

关键词： Nearest neighbor search

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A Blockchain-Based Approach to Counterfeit Prevention 3

A Blockchain-Based Approach to Counterfeit Prevention

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3rd IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Supriya, M.S. Narang, Mridula G Prajwal, G.K. Shetty, Sohan S Patil, Anurag M S Ramaiah University of Applied Sciences Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350317022

In recent years, the prevalence of counterfeit goods in the industrial sector has increased. The company's reputation, sales, and profitability are impacted by this. In recent times there has been a sudden rise in Blockchain technology all thanks to cryptocurrencies. This rise in the technology helped increase research about Blockchain and its uses in various domains, Blockchain technology being known as tamper proof helps in solving the problem where the integrity is in question. This paper discusses the working and implementation of product counterfeit prevention systems using Blockchain technology. This system uses a product-specific QR code generated by the manufacturer to store the product details and an Ethereum-based Blockchain network to store all the product and transaction details. Using this system the consumer can be completely sure about the product's credibility and the manufacturer can safeguard their business interest by reducing the circulation of fake products which can damage their reputation and financial aspects. © 2023 IEEE.

关键词： Anti-counterfeiting Blockchain Counterfeit products Decentralization Ganache Metamask Truffle

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Multiband strain balanced superlattice material system for third generation infrared detectors

Multiband strain balanced superlattice material system for t...

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2024 IEEE Research and Applications of Photonics in Defense Conference, RAPID 2024

作者： Dehzangi, Arash Robert R. McCormick School of Engineering and Applied Science Northwestern University Department of Electrical and Computer Engineering EvanstonIL United States

ISBN: (纸本)9798350373097

Recent increasing interest in strain balanced Type-II superlattices material causing close attention from industry. Tremendous investment was drawn toward establishing strain balanced superlattice (SLS) as new alternative for infrared photodetectors across the broad range of infrared spectrum. In recent years, SLS material system has shown capability in particular specifications to compete with mature and standard mercury cadmium telluride for mid-wavelength and long-wavelength infrared detection. It has been great interest in SLS material system for applications aligned with the standard of third generation of infrared detectors. In this presentation, some recent progress in three color infrared photodetectors based on SLS material system will be presented. © 2024 IEEE.

关键词： Infrared detectors

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Robust Deep Learning Empowered Real Time Object Detection for Unmanned Aerial Vehicles based Surveillance Applications

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Journal of Mobile Multimedia 2023年第2期19卷 451-476页

作者： Ranjith, C. Prasanna Hardas, Bhalchandra M. Khaja Mohideen, M. Syed Nijil Raj, N. Robert, Nismon Rio Mohan, Prakash Faculty in Information Technology Department University of Technology and Applied Sciences Shinas Oman Electronics Engineirng Dept Shri Ramdeobaba College of Enginering and Management Nagpur India Department of Information Technology University of Technology and Applied Science Salalah Oman Department of Computer Science and Engineering Younus College of Engineering and Technology Kollam India Department of Computer Science Christ University Bangalore India School of Computer Science and Engineering Vellore Institute of Technology Vellore India

Surveillance is a major stream of research in the field of Unmanned Aerial Vehicles (UAV), which focuses on the observation of a person, group of people, buildings, infrastructure, etc. With the integration of real time images and video processing approaches such as machine learning, deep learning, and computer vision, the UAV possesses several advantages such as enhanced safety, cheap, rapid response, and effective coverage facility. In this aspect, this study designs robust deep learning based real time object detection (RDL-RTOD) technique for UAV surveillance applications. The proposed RDL-RTOD technique encompasses a two-stage process namely object detection and objects classification. For detecting objects, YOLO-v2 with ResNet-152 technique is used and generates a bounding box for every object. In addition, the classification of detected objects takes place using optimal kernel extreme learning machine (OKELM). In addition, fruit fly optimization (FFO) algorithm is applied for tuning the weight parameter of the KELM model and thereby boosts the classification performance. A series of simulations were carried out on the benchmark dataset and the results are examined under various aspects. The experimental results highlighted the supremacy of the RDL-RTOD technique over the recent approaches in terms of several performance measures. © 2022 River Publishers.

关键词： computer vision deep learning image processing object detection Surveillance unmanned aerial vehicles

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Approaches for Solving a Dynamic Stacking Problem in Uncertain Environments 17

Approaches for Solving a Dynamic Stacking Problem in Uncerta...

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17th International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2023

作者： Boecke, Sarah Logofatu, Doina Frankfurt University of Applied Sciences Department of Computer Science and Engineering Frankfurt am Main Germany

ISBN: (纸本)9798350338904

Dynamic optimization is of significant practical relevance for production and delivery processes that involve storage systems because of the dynamic nature of their environments. The relocation of products has to be scheduled while adhering to different time constraints. This paper addresses the challenge of developing solution approaches for such dynamic stacking problems in uncertain environments, specifically the environment represented by the "Hotstorage"simulation of the DynStack Competition 2023 that is part of the Genetic and Evolutionary Computation Conference. Building on existing approaches, two new solution approached are introduced: a score-based and a genetic solver. Comparing their performance with each other and with existing approaches shows that the score-based solver outperforms other solvers in regard to specific evaluation criteria while the genetic solver in its current form does not perform as well. © 2023 IEEE.

关键词： Petroleum reservoir evaluation

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