Journal of Intelligent Decision Technologies and Applications (e-ISSN: 3049-0219)

AI-Driven Early Warning Systems for Extreme Climate Events (Floods, Heatwaves, Cyclones)

Nishant Tanna, Nisha Rathore — Wed, 24 Jun 2026 00:00:00 +0000

Climate change has intensified the frequency and severity of extreme weather events, including floods, heatwaves, and cyclones, posing unprecedented challenges to human societies and ecosystems. Traditional Numerical Weather Prediction (NWP) models, while foundational, often suffer from high computational costs and limited skill at local spatial scales. The advent of Artificial Intelligence (AI) — particularly deep learning, ensemble methods, and hybrid physics-informed neural networks — has ushered in a new paradigm for climate event prediction and early warning. This paper presents a comprehensive review of AI-driven Early Warning Systems (EWS) for floods, heatwaves, and cyclones. They examine the data ecosystems (satellite, IoT, reanalysis), model architectures (LSTM, CNN, GNN, Transformers, diffusion models), and system integration strategies employed globally. Performance comparisons are presented, key research gaps identified, and future directions proposed. Our analysis demonstrates that AI-enhanced EWS can reduce false negative rates by up to 30% compared with conventional methods, improve lead time by several hours, and enable equitable, low-bandwidth dissemination in resource-constrained regions. The review synthesises over 30 key studies and situates them within a unified framework to guide future research and operational deployment.

Globe Lens: An AI-powered Multimodal Travel Assistance System for International Travellers

Sat, 30 May 2026 00:00:00 +0000

The language barrier, cultural diversity, real-time navigation requirements, and the general plethora of local customs and regulations among countries have complicated international travel. Conventional traveling support devices tend to work in isolation—providing translation, maps or suggestions, but seldom combine these capabilities into a single, smart experience. Globe Lens is a proposed AI-based multimodal travel assistance system that will be a robust global traveller digital assistant. The system uses large language models (LLMs), computer vision, speech recognition, and real-time geospatial information to offer context-sensitive, on-command assistance in various modalities such as text, voice and image inputs. Its core functions are real-time visual translation of signs and menus using the camera, voice-activated conversation in 100-plus languages, AI-powered itinerary planning based upon the tastes and preferences of the user and the real-time environment, cultural etiquette advice, emergency response navigation, and currency and unit conversion. Globe Lens will use a modular microservices model implemented on cloud infrastructure that allows scaling and provides offline backup services in low-connectivity areas. Early system tests reveal that there is high accuracy in object-based translating exercises and high ratings of user satisfaction in simulated travel situations. The study includes the system design, methodology, literature context, and discussion of results and future research directions.

A Survey on Automation and its Impact on Employment and Skill Transformation in the IT Sector

Paripoorani G, Anand TR — Wed, 24 Jun 2026 00:00:00 +0000

Technologies in automation driven by Artificial Intelligence (AI), Machine Learning (ML), and Robotic Process Automation (RPA) are revolutionizing the Information Technology (IT) industry. Automation is not only changing productivity, operational efficiency, and service delivery in the IT sector but also affecting employment. This study focuses on the impact of automation on IT employment, considering both the negative and positive effects. Automation in IT is affecting employment in terms of job destruction in routine and rule-based jobs, as well as job creation in emerging areas such as AI engineering, cloud computing, and cybersecurity. According to this research, there is a rising need for high-level technical skills, critical thinking, and reskilling among IT professionals. The results show that automation is not destroying jobs but changing their nature and structure in organizations. With the evolution of automation technologies in the IT sector, the workforce must learn to adapt to such changes through continuous learning and skill development.