Sachin Kumar  Gupta

Dr. Sachin Kumar Gupta


Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 August 2020 in International Journal of Disaster Risk Reduction
Verified
Journal Article
Closed access
AKAmina Khan
Amina Khan
SGSumeet Gupta
Sumeet Gupta
SGSachin Kumar Gupta
Sachin Kumar Gupta

14 April 2022 in Journal of Field Robotics
Verified
Journal Article
Closed access
AKAmina Khan
Amina Khan
SGSumeet Gupta
Sumeet Gupta
SGSachin Kumar Gupta
Sachin Kumar Gupta

7 October 2020 in Transactions on Emerging Telecommunications Technologies
Verified
Journal Article
Closed access
PDF file
FSFarheen Syed
Farheen Syed
SGSachin Kumar Gupta
Sachin Kumar Gupta
SASaeed Alsamhi
Saeed Alsamhi
Mamoon RashidMamoon Rashid
Mamoon Rashid
XLXuan Liu
Xuan Liu

12 September 2022 in Computer Methods and Programs in Biomedicine
Verified
Journal Article
Closed access
Santosh KumarSantosh Kumar
Santosh Kumar
MCMithilesh Kumar Chaube
Mithilesh Kumar Chaube
SASaeed Alsamhi
Saeed Alsamhi
SGSachin Kumar Gupta
Sachin Kumar Gupta
Mohsen GuizaniMohsen Guizani
Mohsen Guizani
Giancarlo FortinoGiancarlo Fortino
Giancarlo Fortino

30 August 2021 in IEEE Systems Journal
Verified
Journal Article
Closed access
VVVrince Vimal
Vrince Vimal
KSKamred Udham Singh
Kamred Udham Singh
AKAbhishek Kumar
Abhishek Kumar
SGSachin Kumar Gupta
Sachin Kumar Gupta
Mamoon RashidMamoon Rashid
Mamoon Rashid
Sanjeevikumar PadmanabanSanjeevikumar Padmanaban
Sanjeevikumar Padmanaban
Because of the metaphysical shift in the technological era, the world is witnessing machine to machine (M2M) communication. Sensors are omnipresent, owing to which wireless sensor networks (WSNs) are developing as a key enabling technology for the Internet of Things (IoT). M2M interaction poses a severe threat to the lifetime of the network. Clustering plays an essential role in elevating the energy efficiency of the WSN. Particularly, uniform distribution of cluster heads (CHs) is crucial for achieving better network lifetime and uninterrupted sensing from the area under observation. For this, we propose an efficient two-fold clustering algorithm, namely second-fold clustering (SFC). In the first phase, the selection of CH is made based on zonal residual energy and zonal degree of connectivity. In the second phase, the leftover nodes known as isolated nodes are clumped. CH is selected based on the zonal degree of connectivity to ensure that energy is disbursed (almost) uniformly by all the nodes. This uniformity makes it suitable for integration with the IoT. To find out the efficacy of SFC, carried rigorous experimental study out where it is compared to two existing clustering algorithms. The simulation results show that SFC outperforms its counterparts. The results showed that SFC improved network lifetime by approximately 9.6% and 10.2% compared to regional energy-aware clustering scheme and Residual-Low Energy Adaptive Clustering Hierarchy (R-LEACH), respectively.

11 February 2024 in Expert Systems
Verified
Journal Article
Closed access
PKPrabhjot Kaur
Prabhjot Kaur
AMAnand Muni Mishra
Anand Muni Mishra
Nitin GoyalNitin Goyal
Nitin Goyal
SGSachin Kumar Gupta
Sachin Kumar Gupta
Achyut ShankarAchyut Shankar
Achyut Shankar
WVWattana Viriyasitavat
Wattana Viriyasitavat