Notice Board :

Call for Paper
Vol. 7 Issue 7

Submission Start Date:
July 01, 2026

Acceptence Notification Start:
July 10, 2026

Submission End:
July 25, 2026

Final MenuScript Due:
July 31, 2026

Publication Date:
July 31, 2026
                         Notice Board: Call for PaperVol. 7 Issue 7      Submission Start Date: July 01, 2026      Acceptence Notification Start: July 10, 2026      Submission End: July 25, 2026      Final MenuScript Due: July 31, 2026      Publication Date: July 31, 2026




Volume VII Issue VII

Author Name
Om Prakash Jhariya, Durgesh Vishwakarma
Year Of Publication
2026
Volume and Issue
Volume 7 Issue 7
Abstract
This research paper primarily focuses on the integration of photovoltaic (PV) smart grids (SG) and electric vehicles (EVs) with two-way power flow capabilities. This includes charging, discharging, and enhancing power quality using power converters. Given the rising energy demand due to rapid population growth, modernizing the power grid to improve power quality is essential. This modernization allows the energy generated by solar PV systems to be transmitted and stored as excess power in batteries for use during peak load demands. Electric vehicle batteries can be charged during low-demand periods and discharged during peak demand. This dual function enables EVs to serve both as loads and as energy suppliers to the smart grid. Simulation results illustrate the operation of the smart grid-to-vehicle (G2V) system, highlighting improvements in factors such as power factor, power regulation, and harmonic elimination. These enhancements are achieved by constructing a power electronic netwo
PaperID
2026/IJEASM/7/2026/3441

Author Name
Ganesh Kotdiya, Yogesh Patidar
Year Of Publication
2026
Volume and Issue
Volume 7 Issue 7
Abstract
The merging of IoT and fog computing has provided transformative avenues for the improvement of the safety and robustness of industrially used robotic systems. The industrial robots deployed in smart factories, autonomous warehouses and dangerous areas of manufacturing generate petabytes of real-time sensor data that require ultra-low latency processing for worker safety and business continuity. Because of the computational power in cloud-only architectures, these systems are typically latency sensitive (in the milliseconds range) and prone to single-point-of-failures, and thus cannot be easily used for robotic safety applications. This paper provides a complete and meta-analysis of literature on fog-computing-based IoT safety architectures for industrial robots. This review systematically reviews peer-reviewed publications dated between 2015 and 2025 in order to identify dominant architectural paradigms, evaluates communication protocols, surveys strategies for machine learning integr
PaperID
2026/IJEASM/7/2026/3442

Author Name
Megha Verma, Rajesh Chouhan
Year Of Publication
2026
Volume and Issue
Volume 7 Issue 7
Abstract
The use of high-performance concrete (HPC) in the structural optimization of reinforced concrete (RCC) members is a field of contemporary civil engineering with the potential of achieving simultaneously the aforementioned requirements (of high demand for load-bearing capacity, durability and material efficiency). This experimental study focuses on the structural behavioral and optimization possibilities in RCC beams, columns & slabs containing high-performance concrete (HPC) mixes with a wide range of compressive strengths between 60 MPa and 120 MPa along with some supplementary cementitious materials (SCMs) like silica fume, fly ash, & ground granulated blast-furnace slag (GGBS). Monotonic and cyclic load tests were performed on 120 RCC specimens, and the results of deflection, crack width, ductility index, and ultimate load capacity were compared with those of conventional concrete (CC) of characteristic strength between 25 and 30 MPa. We used statistical analysis with regression mod
PaperID
2026/IJEASM/7/2026/3443

Author Name
Rajkumari Ahirwar, Ashish Suryavanshi
Year Of Publication
2026
Volume and Issue
Volume 7 Issue 7
Abstract
Thus, the urgent need for intelligent real-time monitoring solutions that can boost energy yield, reduce downtime and enable predictive maintenance is being created by the rapid proliferation of solar photovoltaic (PV) plants. This empirical study describes the design, implementation and performance assessment of the IoT-based smart monitoring systems that have been developed to collect and store the performance data of grid-connected as well as off-grid solar PV installations. distributed sensor nodes measuring irradiance, module temperature, voltage, current and power output measured using existing cloud based data aggregator, hosted using a web dashboard and mobile application in the proposed system A twelve-month field deployment was undertaken on five PV plants at different scales (5 kWp to 500 kWp) in diverse climatic zones of India. Empirical data gathered from 14,400 hourly observation points underwent descriptive statistics, regression modeling, and fault detection accuracy an
PaperID
2026/IJEASM/7/2026/3444