A
Ashish Kumar Luhach
Researcher at Papua New Guinea University of Technology
Publications - 23
Citations - 474
Ashish Kumar Luhach is an academic researcher from Papua New Guinea University of Technology. The author has contributed to research in topics: Wireless sensor network & Support vector machine. The author has an hindex of 9, co-authored 23 publications receiving 165 citations.
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A novel Software-Defined Drone Network (SDDN)-based collision avoidance strategies for on-road traffic monitoring and management
Adarsh Kumar,Rajalakshmi Krishnamurthi,Anand Nayyar,Ashish Kumar Luhach,Mohammad S. Khan,Anuraj Singh +5 more
TL;DR: This work has considered the collision-free drone-based movement strategies for road traffic monitoring using Software Defined Networking (SDN).
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Energy efficient optimal parent selection based routing protocol for Internet of Things using firefly optimization algorithm
Sankar Sennan,Ramasubbareddy Somula,Ashish Kumar Luhach,Ganesh Gopal Deverajan,Waleed S. Alnumay,Noor Zaman,Uttam Ghosh,Pradip Kumar Sharma +7 more
TL;DR: This article proposes energy efficient optimal parent selection in RPL (EEOPS‐RPL) using firefly optimization algorithm to extend the lifespan of the IoT network.
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IOT based Air Quality Monitoring System Using MQ135 and MQ7 with Machine Learning Analysis
TL;DR: This paper deals with measuring the Air Quality using Mq135 sensor along with Carbon Monoxide CO using MQ7 sensor using Machine Learning analysis and proviing a reducement of the cost of components versus the state of the art.
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Energy and Delay Aware Data Aggregation in Routing Protocol for Internet of Things.
Sankar Sennan,Sathiyabhama Balasubramaniyam,Ashish Kumar Luhach,Somula Ramasubbareddy,Naveen Chilamkurti,Yunyoung Nam +5 more
TL;DR: This work proposes Energy and Delay Aware Data aggregation in Routing Protocol (EDADA-RPL) for IoT, which offers good performance in terms of network lifetime, delay, and packet delivery ratio.
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A Neuro-fuzzy approach for user behaviour classification and prediction
Atta-ur-Rahman,Sujata Dash,Ashish Kumar Luhach,Naveen Chilamkurti,Seungmin Baek,Yunyoung Nam +5 more
TL;DR: A neuro-fuzzy approach for the classification and prediction of user behaviour is proposed and the scheme is found to be promising in terms of classification as well as prediction accuracy.