Edge-Intelligent IoT: Adaptive Context-Aware Resource Orchestration for Ultra-Low-Latency Systems M. Veeresh Babu, U Rakesh, S Saduqulla, Ajanthaa Lakkshmanan 7th International Conference on Mobile Computing and Sustainable Informatics Icmcsi 2026, 2026 The accelerated growth of Internet of Things (IoT) requires smart systems that can address the heterogenous resources and guarantee ultra-low latency to mission-critical systems. It will be described in this paper as an Edge-Intelligent IoT architecture allowing adaptive, context-sensitive resource coordination with lightweight machine learning on the network edge. The system takes into consideration dynamic contextual parameters such as workload patterns, mobility variations and network conditions to decide on the real time offloading and resource allocation decisions. The optimization of latency, energy usage, fairness of resources is made through reinforcement learning, and federated learning optimizes global intelligence without exposing raw data. Simulations with a wide scale indicate that the proposed solution is much faster and uses less energy than the conventional cloud-centric and static edge schemes. Scalability, responsiveness, and Quality of Service are also enhanced in the framework, which is compatible with next-generation IoT settings like autonomous vehicles, smart manufacturing and industrial automation
Computational Literary Analysis in the Age of AI: Transforming Textual Interpretation Through Artificial Intelligence & Machine Learning M. Sirish Kumar, Srinivasulu Sirisala, R Yamuna, B. Ramakantha Reddy, P. Jaya Prakash, U Rakesh Proceedings of the 9th International Conference on Electronics Communication and Aerospace Technology Iceca 2025, 2025 Artificial intelligence is transforming literary studies by enabling large-scale textual analysis and pattern recognition previously impossible through traditional methods. This chapter examines AI applications in literary analysis, including natural language processing, machine learning, and deep learning approaches. Through methodological review and case studies, we demonstrate how AI enhances hermeneutic approaches while addressing challenges of algorithmic bias, interpretive authority, and ethical implementation. Our findings indicate that AI-augmented analysis reveals hidden textual patterns and supports comprehensive interpretations across vast corpora when properly implemented with human oversight. However, significant challenges remain in addressing bias, maintaining interpretive nuance, and preserving humanistic values in computational literary scholarship.
Route Optimization to Manage the Medical Waste in Real-Time International Journal of Intelligent Systems and Applications in Engineering, 2024
An Edge Artificial Intelligence Federated Recommender System for Virtual Classrooms M. Sirish Kumar, T. Rupa Rani, U. Rakesh, Dyavarashetty Sunitha, G. Sunil Kumar Model Optimization Methods for Efficient and Edge AI Federated Learning Architectures Frameworks and Applications, 2024 Recommender systems are becoming more and more popular, from social networking sites to e-commerce. They offer connections, news, information, or interesting goods. The federated recommender system described in this research uses data from many online learning platforms to provide tailored recommendations. The overarching educational goal is to allow educational institutions will provide a Web 2.0 dashboard that incorporates free Cloud resources with paid content from internal learning management systems. The federated recommender system's essential components, including its recognized architecture, the common data model that was utilized to collect information from various learning platforms, and the suggestion display widget, are described in the paper.
Develop a 7 Layers Convolution Neural Network and IoT-Based Garbage Classification System International Journal of Intelligent Systems and Applications in Engineering, 2023
Classification, Collection, and Notification of Medical Waste Using IoT Based Smart Dust Bins Uppala Rakesh, V. Ramya, V. Senthil Murugan Ingenierie Des Systemes D Information, 2023 Hospitals generate a significant amount of highly hazardous medical waste.Waste collectors were now responsible for the majority of waste separation.Currently, hazardous medical waste, including substrate materials, syringes, and other items were separated manually, causing serious problems.Automatic waste separation is proposed for the separation of biowaste produced in hospitals.When waste disposal is identified, the treadmill is moved by an external motor.These wastes would be sent to the Sensing and Classification Units.The source image is captured, preprocessed, median filtered, contrast adjusted, and then classified in five steps.After the steps, the outcome would be assessed using the characteristics collected from the Grey Ordered Model (GOM) and transferred to the trash after the separation procedure.To determine the level of waste in dustbins, an infrared sensor, a moisture sensor, a pressure sensor, and an ultrasonic sensor are used.
RECENT SCHOLAR PUBLICATIONS
Edge-Intelligent IoT: Adaptive Context-Aware Resource Orchestration for Ultra-Low-Latency Systems DA M. Veeresh Babu,U Rakesh,S Saduqulla 7th International Conference on Mobile Computing and Sustainable Informatics … , 2026 2026
Computational Literary Analysis in the Age of AI: Transforming Textual Interpretation Through Artificial Intelligence & Machine Learning MS Kumar, S Sirisala, R Yamuna, BR Reddy, PJ Prakash, U Rakesh 2025 9th International Conference on Electronics, Communication and … , 2025 2025
An Edge Artificial Intelligence Federated Recommender System for Virtual Classrooms GSK M. Sirish Kumar, T. Rupa Rani, U. Rakesh, Dyavarashetty Sunitha Model Optimization Methods for Efficient and Edge AI: Federated Learning … , 2024 2024
Route Optimization to Manage the Medical Waste in Real-Time DVSM U.Rakesh, Dr.V.Ramya International Journal of Intelligent Systems And Applications In Engineering … , 2023 2023 Citations: 3
Develop a 7 Layers Convolution Neural Network and IoT-Based Garbage Classification System DVSM U.Rakesh, Dr.V.Ramya International Journal of Intelligent Systems And Applications In Engineering … , 2023 2023 Citations: 9
Classification, Collection, and Notification of Medical Waste Using IoT Based Smart Dust Bins. U Rakesh, V Ramya, VS Murugan Ingénierie Des Systèmes D'information 28 (1) , 2023 2023 Citations: 8
EIWMS: Enhanced Intelligent Warehouse Monitoring Systems 4.0 DVSM U.Rakesh, Dr.V.Ramya European Journal of Molecular & Clinical Medicine 7 (Issue 10), 2066-2076 , 2020 2020
Super Resolution Image Generation Using Wavelet Domain Inter Polation with Edge Extraction Via A Sparse Representation U Rakesh International Journal of Innovative Science, Engineering & Technology 2 (8) , 2015 2015
MOST CITED SCHOLAR PUBLICATIONS
Develop a 7 Layers Convolution Neural Network and IoT-Based Garbage Classification System DVSM U.Rakesh, Dr.V.Ramya International Journal of Intelligent Systems And Applications In Engineering … , 2023 2023 Citations: 9
Classification, Collection, and Notification of Medical Waste Using IoT Based Smart Dust Bins. U Rakesh, V Ramya, VS Murugan Ingénierie Des Systèmes D'information 28 (1) , 2023 2023 Citations: 8
Route Optimization to Manage the Medical Waste in Real-Time DVSM U.Rakesh, Dr.V.Ramya International Journal of Intelligent Systems And Applications In Engineering … , 2023 2023 Citations: 3
Edge-Intelligent IoT: Adaptive Context-Aware Resource Orchestration for Ultra-Low-Latency Systems DA M. Veeresh Babu,U Rakesh,S Saduqulla 7th International Conference on Mobile Computing and Sustainable Informatics … , 2026 2026
Computational Literary Analysis in the Age of AI: Transforming Textual Interpretation Through Artificial Intelligence & Machine Learning MS Kumar, S Sirisala, R Yamuna, BR Reddy, PJ Prakash, U Rakesh 2025 9th International Conference on Electronics, Communication and … , 2025 2025
An Edge Artificial Intelligence Federated Recommender System for Virtual Classrooms GSK M. Sirish Kumar, T. Rupa Rani, U. Rakesh, Dyavarashetty Sunitha Model Optimization Methods for Efficient and Edge AI: Federated Learning … , 2024 2024
EIWMS: Enhanced Intelligent Warehouse Monitoring Systems 4.0 DVSM U.Rakesh, Dr.V.Ramya European Journal of Molecular & Clinical Medicine 7 (Issue 10), 2066-2076 , 2020 2020
Super Resolution Image Generation Using Wavelet Domain Inter Polation with Edge Extraction Via A Sparse Representation U Rakesh International Journal of Innovative Science, Engineering & Technology 2 (8) , 2015 2015
