Intelligent Deep Learning Enabled Human Activity Recognition for Improved Medical Services

Human Activity Recognition(HAR)has been made simple in recent years,thanks to recent advancements made in Artificial Intelligence(AI)techni-ques.These techniques are applied in several areas like security,surveillance,healthcare,human-robot interaction,and entertainment.Since wearable sensor-based HAR system includes in-built sensors,human activities can be categorized based on sensor values.Further,it can also be employed in other applications such as gait diagnosis,observation of children/adult’s cognitive nature,stroke-patient hospital direction,Epilepsy and Parkinson’s disease examination,etc.Recently-developed Artificial Intelligence(AI)techniques,especially Deep Learning(DL)models can be deployed to accomplish effective outcomes on HAR process.With this motivation,the current research paper focuses on designing Intelligent Hyperparameter Tuned Deep Learning-based HAR(IHPTDL-HAR)technique in healthcare environment.The proposed IHPTDL-HAR technique aims at recogniz-ing the human actions in healthcare environment and helps the patients in mana-ging their healthcare service.In addition,the presented model makes use of Hierarchical Clustering(HC)-based outlier detection technique to remove the out-liers.IHPTDL-HAR technique incorporates DL-based Deep Belief Network(DBN)model to recognize the activities of users.Moreover,Harris Hawks Opti-mization(HHO)algorithm is used for hyperparameter tuning of DBN model.Finally,a comprehensive experimental analysis was conducted upon benchmark dataset and the results were examined under different aspects.The experimental results demonstrate that the proposed IHPTDL-HAR technique is a superior per-former compared to other recent techniques under different measures.

Efficient Hybrid Energy Optimization Method in Location Aware Unmanned WSN

The growth of Wireless Sensor Networks(WSNs)has revolutionized thefield of technology and it is used in different application frameworks.Unmanned edges and other critical locations can be monitored using the navigation sensor node.The WSN required low energy consumption to provide a high network and guarantee the ultimate goal.The main objective of this work is to propose hybrid energy optimization in local aware environments.The hybrid proposed work consists of clustering,optimization,direct and indirect communication and routing.The aim of this research work is to provide and framework for reduced energy and trusted communication with the shortest path to reach source to destination in WSN and an extending lifetime of wireless sensors.The proposed Artificial Fish Swarm Optimization algorithm is used for energy optimization in military applications which is simulated using Network Simulator(NS)tool.This work optimizes the energy level and the same is compared with various genetic algorithms(GA)and also the cluster selection process was compared with thefission-fusion(FF)selection method.The results of the proposed work show,improvement in energy optimization,throughput and time delay.

Multivariate Broadcast Encryption with Group Key Algorithm for Secured IoT

The expanding and ubiquitous availability of the Internet of Things(IoT)have changed everyone’s life easier and more convenient.Same time it also offers a number of issues,such as effectiveness,security,and excessive power consumption,which constitute a danger to intelligent IoT-based apps.Group managing is primarily used for transmitting and multi-pathing communications that are secured with a general group key and it can only be decrypted by an authorized group member.A centralized trustworthy system,which is in charge of key distribution and upgrades,is used to maintain group keys.To provide longitudinal access controls,Software Defined Network(SDN)based security controllers are employed for group administration services.Cloud service providers provide a variety of security features.There are just a few software security answers available.In the proposed system,a hybrid protocols were used in SDN and it embeds edge system to improve the security in the group communication.Tree-based algorithms compared with Group Key Establishment(GKE)and Multivariate public key cryptosystem with Broadcast Encryption in the proposed system.When all factors are considered,Broadcast Encryption(BE)appears to become the most logical solution to the issue.BE enables an initiator to send encrypted messages to a large set of recipients in a efficient and productive way,meanwhile assuring that the data can only be decrypted by defining characteristic.The proposed method improves the security,efficiency of the system and reduces the power consumption and minimizes the cost.