Work place: Department of Computer Science and Engineering (AIML), Dayananda Sagar University, Bengaluru, Karnataka-562112, India
E-mail: a.vegifernando@gmail.com
Website:
Research Interests: Computer Vision
Biography
A. Vegi Fernando received her Bachelor’s degree in Computer Science and Engineering in 2004 from Manonmaniam Sundaranar University, Tamil Nadu, India. She obtained her Master of Engineering (M.E) in 2010 from Anna University, Chennai and Doctor of Philosophy (Ph.D) in 2023, both from Anna University, Chennai. She is currently serving as an Associate Professor in the Department of Computer Science and Engineering (AIML) at Dayananda Sagar University, Bengaluru, Karnataka, India. Her research interests include Computer Vision, Natural Language Processing and IoT.
By J. B. Shriram P. Anbalagan A. Vegi Fernando Srikanth Mylapalli
DOI: https://doi.org/10.5815/ijitcs.2026.01.01, Pub. Date: 8 Feb. 2026
Expansion of Internet of Things (IoT) technologies has greatly enhanced monitoring and management of energy systems, especially in Hybrid Renewable Energy Systems (HRES). This paper presents an IoT-based HRES smart grid framework with a modified Brain Storm Optimization (BSO) algorithm for routing optimization and an Improved Quantum Key Management (IQKM) is a quantum inspired protocol for better data security. The enhanced BSO algorithm, hosted in the cloud infrastructure, optimizes IoT sensor data routing paths, thus diminishing packet transmission latency and improving the network throughput. In contrast to conventional BSO techniques, the enhancement is through dynamic cluster refinement and adaptive node prioritization, designed specifically for real-time cloud-integrated energy systems. In order to protect sensitive energy transmission information, the IQKM protocol includes strong quantum-aided encryption processes and dynamic key creation. These enhancements directly counter the dangers of man-in-the-middle and replay attacks, which exceed capabilities of standard encryption approaches by facilitating low-latency, quantum-resistant communication between HRES nodes. Both Photovoltaic (PV) and wind-based energy sources are utilized by the system to provide power consistently, with cloud-based analytics and IoT sensors ensuring real-time monitoring. Experimental testing via the Adafruit platform reports a 23% Packet Delivery Ratio (PDR) enhancement and 17% encryption/decryption delay reduction compared to baseline and traditional routing algorithms. Such findings ensure the potential for stable, secure, and scalable grid performance by the proposed system.
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