Daily Archives: January 22, 2026

Authors: Gopal Ghosh

Abstract: The integration of Artificial Intelligence (AI) in agriculture has transcended traditional applications like precision farming and crop monitoring. This paper explores cutting-edge and unconventional uses of AI, such as predictive climate-resilient agriculture, AI-driven bioengineering, autonomous swarms, and ethical AI for sustainable farming practices. It delves into the role of AI in reshaping the agricultural landscape by optimizing not only productivity but also sustainability and resilience against climate change. The paper concludes with a discussion on future possibilities, challenges, and the need for inclusive AI solutions in agriculture.

Published by: vikaspatanker

Authors: Keshav Jangir, Manish Saini, Rupali Tanwar, Hridyansh Pradhan

Abstract: SNIPP is a smart remote interview platform that allows secure technical assessments through real-time coding and AI evaluation. It includes MediaPipe-based proctoring, role-based question generation, fullscreen enforcement, and automated handling of violations. These features help ensure fair and reliable interviews. The platform uses a full-stack setup with Next.js for both the frontend and backend. It uses Convex for real-time data synchronization, Clerk for secure authentication, and Monaco Editor for an interactive coding environment. It supports conflict-free interview scheduling, automatic email notifications, and real-time updates through Convex mutations. The system allows browser-based code execution across multiple programming languages with a responsive and device-optimized interface. Key features include MediaPipe AI proctoring, AI-generated questions, a 6-strike violation policy, automatic interview termination, and enforced fullscreen mode. It provides detailed violation reports after interviews, while role-based access control helps manage sessions securely and maintains data integrity. Thorough testing confirmed the platform's effectiveness and reliability. It achieved a 100% functional test pass rate and can handle up to 50 concurrent users. The average API response time is 1.5 seconds. The platform is fully secure, implementing JWT-based authentication and input validation, and maintained 99.9% uptime during load testing. SNIPP delivers a scalable, robust solution that reduces scheduling conflicts in remote interviews, removes the need for infrastructure setup for coding assessments, and helps recruiters work efficiently.

DOI: http://doi.org/10.5281/zenodo.18337196

Published by: vikaspatanker

Authors: Walid Bebal, Joydeb Nandi, Taha Ghole, Prof.S.E.Gawali

Abstract: This paper presents HealthAI, a mobile-based per- sonal health advisor application designed to improve preventive healthcare awareness. The application integrates multiple public APIs to deliver real-time weather-based health insights, nutrition analysis, drug safety alerts, and health-related news through a unified mobile interface. A modular client–server architecture is adopted to ensure scalability, reliability, and low response latency. Experimental evaluation demonstrates that the system performs efficiently under varying workloads, making it suitable for real- world mobile health applications.

DOI: http://doi.org/10.5281/zenodo.18428124

Published by: vikaspatanker

Authors: Omkar Dhas, Sarthak Kulthe, Akhilesh Barate, Pruthviraj Zinge, Prof. Sonali Navale. S

Abstract: In this paper, the design of a footstep-based power generation system using piezoelectric sensors is presented. The increasing demand for energy due to rapid population growth has led to the depletion of conventional power resources. Therefore, the utilization of renewable and alternative energy sources has become essential. This proposed system focuses on harvesting mechanical energy generated from human footsteps and converting it into electrical energy. The concept is highly suitable for densely populated countries like India and China, where public places such as railway stations, bus stands, and streets experience continuous human movement. By implementing this system, the mechanical energy produced during walking can be efficiently converted into usable electrical energy.

Published by: vikaspatanker