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Social Cognition Simulation With Large Language Model-Driven Agents, Mingxin Zhang, Jinxuan Wu, Rui Zhu, Yunlong Wang, Wenjuan Meng, Zhe Liu, Xu Li, Xiaolei Chen, Yuxuan Liang, Yi Zheng, Xiangyang Xue Feb 2026

Social Cognition Simulation With Large Language Model-Driven Agents, Mingxin Zhang, Jinxuan Wu, Rui Zhu, Yunlong Wang, Wenjuan Meng, Zhe Liu, Xu Li, Xiaolei Chen, Yuxuan Liang, Yi Zheng, Xiangyang Xue

Journal of System Simulation

Abstract: With the continuous evolution of the capabilities of generative LLMs, their application in social cognition simulation is demonstrating paradigm-shifting potential. Traditional social simulation methods predominantly rely on static rules and simplified behavioral models, making it difficult to capture the dynamic evolution and cultural complexity of human social behavior. LLM-driven agents, equipped with contextual understanding and natural language generation capabilities, are emerging as novel tools for modeling social cognitive mechanisms, enabling the simulation of complex sociopsychological processes such as identity construction, value judgment, and intentional reasoning. This paper briefly introduced the technical foundations of LLMs and highlighted their suitability for …

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Integrated Development Environment For Digital Test Applications Based On Cloud-Edge-End Architecture, Wenguang Yu, Qun Li, Hongjie Dang, Hao Chen, Ping Yang Feb 2026

Integrated Development Environment For Digital Test Applications Based On Cloud-Edge-End Architecture, Wenguang Yu, Qun Li, Hongjie Dang, Hao Chen, Ping Yang

Journal of System Simulation

Abstract: Digital test applications need to be constructed using the unified digital test development tool. After analyzing the features of digital test applications such as large-sample autonomous run, high computational efficiency requirement, and diverse task scenarios, this paper proposes the integrated development environment (IDE) for digital test applications based on cloud-edge-end architecture. The layered expandable architecture, the hybrid integration framework of multi-source heterogeneous models, and the cloud-edge-end collaborative deployment architecture are designed for the IDE of digital test applications. The IDE supports the rapid development, integration, and execution of digital test models and enables development of digital test applications on …

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Research On Chain-Of-Thought Technology For Situational Awareness Based On Modular Reasoning, Hongyuan Ji, Duzheng Qing Feb 2026

Research On Chain-Of-Thought Technology For Situational Awareness Based On Modular Reasoning, Hongyuan Ji, Duzheng Qing

Journal of System Simulation

Abstract: To address issues such as insufficient intelligence of situational understanding in traditional simulation systems, a situational visual question answering dataset was constructed, and a modular reasoning framework was proposed. The SACoT was built, which, under a zero-shot setting, employed expert prompts to guide the model in task decomposition and multimodal information fusion, generating reasoning chains to enhance semantic cognition and interpretability and offering a scalable solution with low computation cost. Experimental results indicate that SACoT improves task allocation, enables models to focus on query-relevant image details, mitigates the fragmentation of chain-of-thought induced by multi-step reasoning, and reduces long-form …

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Simulation Of Robotic Arm Ball-Catching Strategy Based On Curriculum Rl Of Transformer, Ziyao Zhang, Yunfeng Ji Feb 2026

Simulation Of Robotic Arm Ball-Catching Strategy Based On Curriculum Rl Of Transformer, Ziyao Zhang, Yunfeng Ji

Journal of System Simulation

Abstract: Method integrating the PPO algorithm with Transformer network architecture is proposed, and curriculum learning strategy is introduced to solve the difficult training convergence and low efficiency of traditional RL methods in complex and dynamic high-degree-of-freedom tasks such as robotic arm ball catching. The Transformer is employed to effectively capture the complex high-dimensional dependency between the robotic arm's state space, ball trajectory, and environmental physical parameters. Curriculum learning progressively increases catching difficulty by designing training tasks from simple to complex objectives. The experimental results show this method increases the ball-catching success rate by over 60% compared to the traditional …

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Research On Uav Target Tracking Algorithm For Simulation Scenarios, Xinyi Li, Zhenfei Wang, Han Wu Feb 2026

Research On Uav Target Tracking Algorithm For Simulation Scenarios, Xinyi Li, Zhenfei Wang, Han Wu

Journal of System Simulation

Abstract: To address the need for automatic UAV tracking of moving targets in simulated experiments, this paper proposed a long-term automatic tracking method based on an improved channel and spatial reliability-aware tracker (CSRT) algorithm. The target edge features were detected using the Laplacian of guided filter (LOGF) through guided filtering and then fused with the histogram of oriented gradient (HOG) and color names (CN) features to enhance the algorithm's discriminative ability for the target. To evaluate the target state, the paper used average peak correlation energy and perceptual hash Hamming distance. When the target was occluded, the paper employed YOLOv8 …

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Distributed Optimization For Integrated Energy Based On Multi-Agent Reinforcement Learning, Caixia Tao, Naikun Chen, Fengyang Gao, Jiangang Zhang Feb 2026

Distributed Optimization For Integrated Energy Based On Multi-Agent Reinforcement Learning, Caixia Tao, Naikun Chen, Fengyang Gao, Jiangang Zhang

Journal of System Simulation

Abstract: To address the energy management and privacy preservation problems faced by the coordinated optimization of distributed integrated energy systems, a distributed coordinated optimization strategy based on the multi-agent proximal policy optimization algorithm was proposed. An energy management model was established under the MDP framework; the electrical and thermal heterogeneous energy characteristics were considered; a multi-region two-layer interaction mechanism was constructed. Under the framework of centralized training and decentralized execution, homomorphic encryption was utilized to avoid privacy leakage during the coordination process, while accurately quantifying individual contributions to mitigate the problem of variance explosion in multi-agent policy evaluation. In the …

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Prediction Of Inflow Wind Field For Large-Scale Wind Turbines Based On Multimodal Hybrid Deep Learning, Jiheng Wang, Yang Hu, Ziqiu Song, Fang Fang, Jizhen Liu Feb 2026

Prediction Of Inflow Wind Field For Large-Scale Wind Turbines Based On Multimodal Hybrid Deep Learning, Jiheng Wang, Yang Hu, Ziqiu Song, Fang Fang, Jizhen Liu

Journal of System Simulation

Abstract: To address the demand for high-precision inflow wind field prediction in large-scale wind turbines, traditional CFD methods suffer from high computational costs and poor real-time applicability. This paper proposed a multimodal hybrid deep learning-based wind field prediction method. The proposed method took turbine operating parameters and far-range wind field images as inputs and generated short-range wind field images as outputs. By employing a U-Net-Transformer-GAN hybrid architecture, the model achieved multi-scale feature extraction, temporal dependency modeling, and highresolution wind field image generation. The vorticity transport equation and Kármán-Howarth turbulence statistics were incorporated as weak constraints to enhance physical consistency, while …

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Llm-Driven Multi-Agent Social Network Simulation: Interdisciplinary Integration And Cutting-Edge Development, Jiting Li, Yi Sun, Yirong Wang, Yiqin Lin, Jun Jia, Gangsong Ding Feb 2026

Llm-Driven Multi-Agent Social Network Simulation: Interdisciplinary Integration And Cutting-Edge Development, Jiting Li, Yi Sun, Yirong Wang, Yiqin Lin, Jun Jia, Gangsong Ding

Journal of System Simulation

Abstract: The breakthrough of LLMs has provided powerful tools for social network research, advancing multi-agent social network simulation into a new era. This review systematically examined recent progress in LLM-driven multi-agent social network simulation research through a integrated perspective of multi-disciplines such as artificial intelligence, psychology, communication studies, and sociology. A three-tiered research system, which has gradually formed in this field and encompassed micro-level individual behaviors, meso-level interactive relations, and macro-level system emergence, was summarized. At the micro-level, research focuses on individual human behavior simulation, and numerous studies are dedicated to developing human-like agents with complex cognitive and affective architectures …

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An Adaptive Robot Path Planning Based On Improved Rea* Algorithm, Ling Zhu, Jing Li, Zhaohui Zhang Feb 2026

An Adaptive Robot Path Planning Based On Improved Rea* Algorithm, Ling Zhu, Jing Li, Zhaohui Zhang

Journal of System Simulation

Abstract: In order to improve the computational efficiency and path smoothness in a robot's global path planning, an adaptive robot path planning strategy based on an improved unilateral rectangle expansion A*(REA*) algorithm was proposed. The robot's operational safety was ensured by setting a buffer around obstacles. A passable interval formed by unilateral rectangle expansion was used as the operation unit, and bidirectional alternating search was combined to enhance the path planning efficiency. Inspired by potential field theory, the evaluation function was optimized by introducing a vector form to achieve fast adaptive obstacle avoidance. A new path planning strategy was proposed …

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Evolutionary Game-Based Analysis Of Responses To Hallucinations In Generative Artificial Intelligence, Qiang Yan, Qianyu Zhang, Na Wei Feb 2026

Evolutionary Game-Based Analysis Of Responses To Hallucinations In Generative Artificial Intelligence, Qiang Yan, Qianyu Zhang, Na Wei

Journal of System Simulation

Abstract: The accelerated deployment of generative artificial intelligence, particularly large language models, has amplified the social risks of hallucinations, posing systemic threats to the credibility of the information ecosystem, the effectiveness of users’ cognitive decision-making, and the governance security in the public domain. Research primarily focuses on hallucination mitigation mechanisms at the technical level or the design of regulatory frameworks at the policy level, lacking a systematic theoretical analysis of the evolutionary logic of strategic interactions among the “large language models, users, and regulators” under conditions of bounded rationality. By introducing evolutionary game theory into the field of generative artificial …

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Intelligent Air Combat Decision-Making Method Based On Bigru And Priority Dynamic Sampling, Zhengkun Ding, Jiaqi Liu, Junzheng Xu, Yuezhu Xu, Xingmei Wang Feb 2026

Intelligent Air Combat Decision-Making Method Based On Bigru And Priority Dynamic Sampling, Zhengkun Ding, Jiaqi Liu, Junzheng Xu, Yuezhu Xu, Xingmei Wang

Journal of System Simulation

Abstract: Current multi-agent reinforcement learning algorithms suffer from low efficiency in utilizing experience data and difficulties in setting appropriate learning rates. To address these issues, this paper proposed a BiGRU multi-agent PPO with priority sampling and dynamic learning rate. The algorithm incorporated a BiGRU network to enhance the policy network's ability to model temporal information. A priority partial sampling mechanism was introduced to improve the utilization efficiency of high-value experience data. Additionally, an improved Adam optimizer with dynamic learning rate adjustment was employed to address the challenge of learning rate configuration. Simulation experiment results demonstrate that the algorithm significantly …

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Knowledge-Enhanced Llm-Based Method For Regional Traffic Signal Control, Risheng Xu, Linyao Yang, Yuanqi Qin, Xiao Wang, Changyin Sun Feb 2026

Knowledge-Enhanced Llm-Based Method For Regional Traffic Signal Control, Risheng Xu, Linyao Yang, Yuanqi Qin, Xiao Wang, Changyin Sun

Journal of System Simulation

Abstract: Adaptive traffic signal control (ATSC) is crucial for alleviating regional traffic congestion, yet it faces severe challenges in real-time response to unexpected events and global coordination. The DRL method relies on pure data-driven approaches, suffering from core limitations such as poor generalization, weak interpretability, and a lack of guidance from emergency disposal knowledge, which makes them difficult to meet the demands of complex traffic scenarios. A control system that integrates knowledge-driven and data-optimized approaches was proposed. The GraphRAG was used to construct a dynamic traffic knowledge graph, providing LLMs with real-time updated historical emergency disposal experience and road …

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Scalar Hybrid Meson B̄Gc, Bi̇rten Barsbay İnaç Feb 2026

Scalar Hybrid Meson B̄Gc, Bi̇rten Barsbay İnaç

Turkish Journal of Physics

The scalar hybrid meson Hbc, containing both heavy b and c quarks, represents an intriguing exotic state in QCD. In this article, we investigate its strong decay properties using three-point QCD sum rules. We focus on the two leading decay channels, Hbc → B+ D0 and Hbc → B0 D+, which are expected to dominate the decay dynamics. The B and D mesons produced in these decays each consist of one heavy and one light quark. The strong coupling constants at the corresponding vertices are extracted, and the partial decay widths …

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The Relative Strength Of Paternal Absence, Strong Black Woman Schema, And Self-Esteem In Predicting Resilience Among Black Women, Aqueelah Wheatley Feb 2026

The Relative Strength Of Paternal Absence, Strong Black Woman Schema, And Self-Esteem In Predicting Resilience Among Black Women, Aqueelah Wheatley

Walden Dissertations and Doctoral Studies

The continued rise in single-mother households within Black communities has led to an increase in hyper-independence among Black women, a phenomenon referred to as the strong Black woman schema. Studies have found an association between hyper-independence (i.e., excessive self-reliance and emotional invulnerability) and absent fathers (i.e., due to incarceration or abandonment), forcing Black women to assume the roles of financial provider, caregiver, and community agent. Though studies have found a link between the strong Black woman and negative health outcomes (e.g., emotional distress), other studies have found that strong Black women characterize themselves as independent, empowered, and content individuals, feelings …

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The Patentability Of Ethical Ai: A Spectrum, Rana Matared, Harut Minasian Feb 2026

The Patentability Of Ethical Ai: A Spectrum, Rana Matared, Harut Minasian

Chicago-Kent Journal of Intellectual Property

No abstract provided.

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Outburst Characteristics Of Transient  Low-Mass X-Ray Binary 4u 1608-52, Can Güngör Feb 2026

Outburst Characteristics Of Transient  Low-Mass X-Ray Binary 4u 1608-52, Can Güngör

Turkish Journal of Physics

We present a detailed analysis of the long-term X-ray light curve of 4U 1608–52, focusing on fast-rising exponential-decay (FRED) outbursts, low-intensity states, and quiescent intervals. By calibrating the onset times of the outbursts, we identify three distinct classes for the FRED-type events: (i) the long-high outbursts, exceeding ~50 d in duration with peak count rates above ~40 cnt s-1; (ii) the short-medium outbursts, with durations of ~20 d and peak count rates of ~30-50 cnt s-1; and (iii) the short-low outbursts, also lasting ~20 d but reaching only ~20-30 cnt s-1 at peak. Furthermore, we examine the relation between preoutburst …

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New Measurement And Analysis For The 15N + 11B Elastic Scattering System, Nurlan Amangeldi, İsmai̇l Boztosun, Dauren Soldatkhan, Bakytbek Mauyey, Kanat Makhanov, Raimbek Akhat, Aida Anuar, Gani Yergaliuly Feb 2026

New Measurement And Analysis For The 15N + 11B Elastic Scattering System, Nurlan Amangeldi, İsmai̇l Boztosun, Dauren Soldatkhan, Bakytbek Mauyey, Kanat Makhanov, Raimbek Akhat, Aida Anuar, Gani Yergaliuly

Turkish Journal of Physics

New experimental data on the elastic scattering of the nuclear process 15N+11B at an energy of Elab=26.25 MeV were obtained on the DC-60 cyclotron of the INP RK. Based on a semi-microscopic analysis of the interaction of an accelerated 15N ion with 1p-shell nuclei 11B the effectiveness of the new B3Y-Fetal potential was studied. . The difference between the B3Y-Fetal potential and the traditional Yukawa potentials (M3Y-Reid and M3Y-Paris) is that its density-dependent parameters are determined from the saturation condition of nuclear matter at low energy. Analysis was performed on double folding optical model (DFOM) and so no for other …

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A Semantic Knowledge-Enhanced Assessment Method For Spectrum Effectiveness Of Low Earth Orbit Constellations, Yiqing Liu, Qiuyang Zhang, Chunyu Liu, Yao Xue, Zhiwei Wei, Yan Feng Feb 2026

A Semantic Knowledge-Enhanced Assessment Method For Spectrum Effectiveness Of Low Earth Orbit Constellations, Yiqing Liu, Qiuyang Zhang, Chunyu Liu, Yao Xue, Zhiwei Wei, Yan Feng

Journal of System Simulation

Abstract: In order to scientifically assess the spectrum effectiveness of low earth orbit constellations, the problems of insufficient adaptability of the traditional assessment framework and inaccurate estimation of KPIs under sparse data conditions were solved, a semantic knowledge-enhanced assessment method for spectrum effectiveness of low earth orbit constellations was proposed. A comprehensive multi-level, all band, and multi-dimensional spectrum effectiveness assessment framework covering link level, system level, geographical level, and service application level was constructed. A KPI intelligent prediction agent model integrating semantic knowledge and machine learning was proposed to quantify text-like design parameters using SentenceTransformer, so as to rapidly …

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Simulation Method For Multi-Crew Construction Processes Based On Large Language Model-Powered Agent, Yifan Wang, Bin Yang, Congjun Wang Feb 2026

Simulation Method For Multi-Crew Construction Processes Based On Large Language Model-Powered Agent, Yifan Wang, Bin Yang, Congjun Wang

Journal of System Simulation

Abstract: Traditional construction simulation methods typically rely on predefined rules or static scheduling mechanisms, making it difficult to simulate interactive decision-making under complex constraints by dynamically adapting multi-crew construction scenarios. As a result, workforce idleness caused by process dependencies and spatial occupation fails to be solved. A simulation method for multicrew construction processes based on a LLM-powered agent was proposed. The distributed crew agents endowed with construction scenario understanding and reasoning capabilities were constructed, as well as a centralized project manager agent. A “single-manager and multiple-crew” decision-making mechanism for multi-agent interaction in construction was designed. Autonomous decision-making and coordination mechanism …

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A Civilization’S Soul : Positioning Architectural Works In The Argument For Greater Restrictions On Ai Training, Alexandria B. Noble Feb 2026

A Civilization’S Soul : Positioning Architectural Works In The Argument For Greater Restrictions On Ai Training, Alexandria B. Noble

Chicago-Kent Journal of Intellectual Property

No abstract provided.

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Algorithmic Chopin—Musical Authorship In The Age Of Artificial Intelligence, Eyal Brook Feb 2026

Algorithmic Chopin—Musical Authorship In The Age Of Artificial Intelligence, Eyal Brook

Chicago-Kent Journal of Intellectual Property

No abstract provided.

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Resource-Efficient Continuous Learning Framework For Edge Real-Time Video Analytics, Shuxia Wu, Junjie Zhang, Delong Chen, Zheyi Chen Feb 2026

Resource-Efficient Continuous Learning Framework For Edge Real-Time Video Analytics, Shuxia Wu, Junjie Zhang, Delong Chen, Zheyi Chen

Journal of System Simulation

Abstract: By deploying lightweight models at the network edge, edge systems can provide services of real-time video analytics. However, due to the data drift caused by the discrepancy between model training and actual deployment, it is challenging to construct lightweight models that match real-world environments. To address this challenge, a resource-efficient continuous learning framework for edge real-time video analytics (CL4VA) was proposed. A region of interest-granularity predictor for accuracy degradation was introduced to efficiently select key samples from real-time video streams. A two-layer mixed sample pool was constructed to adaptively trigger the model's continuous learning and avoid the issue of …

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Reinforcement Learning Based Method For Uav Team Orienteering Optimization Under Multi-Constraint Condition, Can Yang, Kai Chen, Feng Zhu Feb 2026

Reinforcement Learning Based Method For Uav Team Orienteering Optimization Under Multi-Constraint Condition, Can Yang, Kai Chen, Feng Zhu

Journal of System Simulation

Abstract: Traditional optimization methods struggle with efficiency, while reinforcement learning approaches often yield low solution quality and high training costs. In response, this paper proposes an attention mechanism-based reinforcement learning method. A dynamic attention strategy network with multi-information fusion is designed to improve solution quality. A visibility-graph approach is employed to simplify threat zone constraints and speed up convergence, and a decoding sequence reordering mechanism is introduced for further performance optimization of the solution. The simulation results show that the method generates high-quality solutions within milliseconds, achieving total rewards that approach or even surpass those obtained by traditional solvers …

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Strike Strategy Planning Method Of Unmanned Ground Vehicles Based On Improved Ppo Algorithm, Bingkun Wang, Yue Wang, Mei Yang, Pengnian Zhang, Bohao Fan, Jie Tang Feb 2026

Strike Strategy Planning Method Of Unmanned Ground Vehicles Based On Improved Ppo Algorithm, Bingkun Wang, Yue Wang, Mei Yang, Pengnian Zhang, Bohao Fan, Jie Tang

Journal of System Simulation

Abstract: An improved PPO algorithm based on the hybrid action space and gated recurrent unit (GRU) is proposed to address the limitations of predefined strike rules in maximizing the hitting accuracy of unmanned ground vehicles and the difficult coupling and optimization of continuous motion planning and discrete strike decision-making. The environmental model and target model are built for the process of unmanned ground vehicles' strike missions, coupled with a three-layer model for unmanned ground vehicles that fuses kinematic constraints, situational awareness, and dynamic decision-making. Two distinct policy networks are employed, including the continuous motion planning network for path planning, and …

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Knowledge Closed-Loop Driving-Based Intelligent Game Confrontation Simulation, Quan Liu, Yu Wang, Linyue Liu, Hao Chen, Jian Huang Feb 2026

Knowledge Closed-Loop Driving-Based Intelligent Game Confrontation Simulation, Quan Liu, Yu Wang, Linyue Liu, Hao Chen, Jian Huang

Journal of System Simulation

Abstract: For human-machine intelligence integration and collaborative intelligence enhancement, a “knowledge-model-data-knowledge” closed-loop paradigm for combat simulation is proposed to guide the design of a DRL-based game confrontation simulation architecture. By building a combat priori knowledge-guided DRL agent model, mining and analyzing the time series data of agent interactions generated during simulations, and extracting combat posterior knowledge that expands the cognition boundaries of commanders, the knowledge closed-loop driving mechanism for intelligent combat simulations is achieved. The experimental results indicate that the proposed mechanism can effectively endow the combat simulation system with intelligence growth capabilities, providing valuable reference for the deepening …

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Intelligent Decision-Making Method In Imbalanced Air Combat Based On Asymmetric Self-Play, Wei Zheng, Jiahao Tang, Xiaoping Xiong, Xin Fan Feb 2026

Intelligent Decision-Making Method In Imbalanced Air Combat Based On Asymmetric Self-Play, Wei Zheng, Jiahao Tang, Xiaoping Xiong, Xin Fan

Journal of System Simulation

Abstract: To solve the problem of strategy convergence caused by role homogenization in traditional self-play for imbalanced air combat, an intelligent decision-making method based on asymmetric selfplay was proposed. This method decoupled tactics from control by employing a hierarchical reinforcement learning framework and designed differentiated reward functions for advantaged and disadvantaged sides. Bidirectional independent policy pools were constructed to promote the co-evolution of strategies. The proximal policy optimization algorithm was utilized to train the model. Experiments in 1v1 weapon-imbalanced and 2v1 numerically-imbalanced scenarios demonstrate that compared to symmetric self-play, the proposed method increases the kill rate of the advantaged …

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Agent-Based Pathfinding Method For Indoor Fire Emergency Evacuation, Ao Tian, Jianqin Zhang, Zheng Wen, Chaonan Hu, Hong Zhao, Bo Shen Feb 2026

Agent-Based Pathfinding Method For Indoor Fire Emergency Evacuation, Ao Tian, Jianqin Zhang, Zheng Wen, Chaonan Hu, Hong Zhao, Bo Shen

Journal of System Simulation

Abstract: To improve emergency evacuation efficiency and reduce casualties in dynamic fire scenarios, a real-time path re-planning method based on agents and dynamic A* algorithm framework is proposed. The behavior and actions of the agent is modeled. A reward function is designed, and an agent-based evacuation framework is constructed. Based on fire simulation data, a dynamic cost network involving parameters such as thermal radiation, smoke visibility, and CO concentration is constructed to achieve spatiotemporally continuous modeling of fire environments. By optimizing the composite cost function through dynamic weight allocation, combined with an improved heuristic function and dynamic search mechanism, local …

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The Parthenon, February 18, 2026, Baylee Parsons, Kaitlyn Fleming, Abby Ayes, Ella Hatfield, Davina Synder, Scott Price, Trista Honaker Feb 2026

The Parthenon, February 18, 2026, Baylee Parsons, Kaitlyn Fleming, Abby Ayes, Ella Hatfield, Davina Synder, Scott Price, Trista Honaker

The Parthenon

No abstract provided.

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Hybrid 3d Modelling Framework For Indoor Navigation Using Federated Learning And Internet Of Things-Enabled Edge Devices, Noopur Tyagi, Jaiteg Singh, Saravjeet Singh, Ahmad Ali Alzubi, Farman Ali, Sukhjit Singh Sehra, Babar Shah Feb 2026

Hybrid 3d Modelling Framework For Indoor Navigation Using Federated Learning And Internet Of Things-Enabled Edge Devices, Noopur Tyagi, Jaiteg Singh, Saravjeet Singh, Ahmad Ali Alzubi, Farman Ali, Sukhjit Singh Sehra, Babar Shah

All Works

Background There has been a recent trend towards using three-dimensional (3D) models to enhance spatial awareness and maximize resource utilization in complex environments. 3D building model can be used in various applications, such as real-time guidance and tracking the positions of individuals in multi storied buildings. Cities are now being modeled and studied in three dimensions as an improved method of urban planning. Method This study proposes an advanced indoor navigation framework that combines 3D modelling, federated learning (FL), and Internet of Things (IoT) integration to deliver reliable floor-level localization and real-time guidance. In Phase 1, highly accurate 3D models …

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Cover And Contents Feb 2026

Cover And Contents

Turkish Journal of Physics

No abstract provided.

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