Volume 1, Issue 2

February 2026 — 4 Published Articles

Cover for Volume 1, Issue 2

Volume 1, Issue 2

February 2026 • 4 Articles

Modern Explorations in Research, Innovation, and Transformation (MERIT)

🔓 Open Access🔗 DOI Assigned
Health Informatics & BlockchainResearch ArticleVol. 1, Issue 2, 2026

Blockchain-Based Secure Medical Record Management System

Prof. Amit Desai, Dr. Kavita Joshi

Registration ID: MERIT-2026-0002DOI: 10.55421/merit.2026.0002 (Submitted to Crossref)

We present a novel blockchain-based framework for managing electronic health records that ensures data integrity, patient privacy, and interoperability across healthcare institutions. The proposed system utilizes Hyperledger Fabric and achieves transaction throughput of 3,000 TPS while maintaining HIPAA compliance.

Read MoreSearch in Googlehttps://meritjournal.org/publications/article/MERIT-2026-0002
Hydrogeology & Urban StudiesCase StudyVol. 1, Issue 2, 2026

Impact of Urbanization on Groundwater Quality: A Case Study of Chennai Metropolitan Area

Prof. Venkataraman S., Dr. Kalyani Mohan, Mr. Ashwin Kumar

Registration ID: MERIT-2026-0010DOI: 10.55421/merit.2026.0010 (Submitted to Crossref)

This study assesses the impact of rapid urbanization on groundwater quality in the Chennai Metropolitan Area through comprehensive hydrochemical analysis of 120 groundwater samples.

Read MoreSearch in Googlehttps://meritjournal.org/publications/article/MERIT-2026-0010
Smart Agriculture & IoTResearch ArticleVol. 1, Issue 2, 2026

IoT-Enabled Smart Irrigation System for Precision Agriculture

Dr. Govind Menon, Er. Ravi Shankar, Dr. Pooja Gupta

Registration ID: MERIT-2026-0008DOI: 10.55421/merit.2026.0008 (Submitted to Crossref)

We design and implement an IoT-based smart irrigation system using ESP32 microcontrollers, soil moisture sensors, and weather API integration.

Read MoreSearch in Googlehttps://meritjournal.org/publications/article/MERIT-2026-0008
Agricultural Engineering & AIResearch ArticleVol. 1, Issue 2, 2026

Machine Learning Approaches for Predicting Crop Yield in Semi-Arid Regions

Dr. Priya Sharma, Dr. Rajesh Kumar, Ms. Anita Verma

Registration ID: MERIT-2026-0001DOI: 10.55421/merit.2026.0001 (Submitted to Crossref)

This study explores advanced machine learning techniques including Random Forests and Deep Neural Networks for predicting crop yields in semi-arid agricultural regions of India. Using satellite imagery and historical weather data spanning 15 years, our models achieve a prediction accuracy of 94.3%, significantly outperforming traditional statistical methods.

Read MoreSearch in Googlehttps://meritjournal.org/publications/article/MERIT-2026-0001

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