Intelligent Data Communication Technologies and Internet of Things

Dr. D. Jude Hemanth received his B.E degree in ECE from Bharathiar University in 2002, M.E degree in communication systems from Anna University in 2006 and Ph.D. from Karunya University in 2013. His research areas include Computational Intelligence and Image processing. He has authored more than 120 research papers in reputed SCIE indexed International Journals and Scopus indexed International Conferences. His Cumulative Impact Factor is more than 150. He has published 33 edited books with reputed publishers such as Elsevier, Springer and IET. Dr. Danilo Pelusi received the Ph.D. degree in Computational Astrophysics from the University of Teramo, Italy. Associate Professor at the Faculty of Communication Sciences, University of Teramo, he is an Associate Editor of IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Access, International Journal of Machine Learning and Cybernetics (Springer) and Array (Elsevier). Guest editor for Elsevier, Springer and Inderscience journals, he served as program member of many conferences and as editorial board member of many journals. His research interests include Fuzzy Logic, Neural Networks, Information Theory and Evolutionary Algorithms. Publication Link: https://scholar.google.it/citations?user=weczOsMAAAAJ&hl=it Dr. Chandrasekar Vuppalapati is a Software IT Executive with diverse experience in Software Technologies, Enterprise Software Architectures, Cloud Computing, Big Data Business Analytics, Internet of Things (IoT), and Software Product & Program Management. Chandra held engineering and Product leadership roles at GE Healthcare, Cisco Systems, Samsung, Deloitte, St. Jude Medical, and Lucent Technologies, Bell Laboratories Company. Chandra teaches Software Engineering, Mobile Computing, Cloud Technologies, and Web & Data Mining for Master’s program in San Jose State University. Additionally, Chandra held market research, strategy and technology architecture advisory roles in CiscoSystems, Lam Research and performed Principal Investigator role for Valley School of Nursing where he connected Nursing Educators & Students with Virtual Reality technologies. Chandra has functioned as Chair in numerous technology and advanced computing conferences such as: IEEE Oxford, UK, IEEE Big Data Services 2017, San Francisco USA and Future of Information and Communication Conference 2018, Singapore. Chandra graduated from San Jose State University Master’s Program, specializing in Software Engineering, and completed his Master of Business Administration from Santa Clara University, Santa Clara, California, USA.

• An Optimized Convolutional Neural Network Model for Wild Animals Detection Using Filtering Techniques and Different Opacity Levels.- Audio Denoising using Deep Neural Networks.- Concept and Development of Triple Encryption Lock System.- Ease and Handy Household Water Management System.- Cotton Price Prediction and Cotton Disease Detection Using Machine Learning.- Intrusion Detection System intensive on Securing IoT Network Environment based on Machine Learning Strategy.- Artificial Intelligence based Phonocardiogram: Classification using Cepstral Features.- Analysis of IoT based Healthcare Framework System using Machine Learning. - A Gender Recognition System from Human Face Images using VGG16 with SVM.- Deep Learning Aproach for RPL Wormhole Attack.- Autonomous Driving Vehicle System Using LiDAR Sensor.- Machine Learning Based Approach for Therapeutic Outcome Prediction of Autism Children.- A Survey on Image Emotion Analysis for Online Reviews.- IoT based Electricity Theft MonitoringSystem.- Prediction of Solar Power Using Machine Learning Algorithm.- Detecting Fake News using Machine Learning.- A Survey on Blockchain enabled by Artificial Intelligence.- Methodologies to Ensure Security and Privacy of an Enterprise Healthcare Data Warehouse.- Emotion and Collaborative based Music Recommendation System.- Interactive Agricultural Chatbot based on Deep Learning.- Hybrid Beamforming for Massive MIMO Antennas under 6 GHz Mid-Band.- A Robust Authentication and Authorization System Powered by Deep Learning and Incorporating Hand Signals.