Samudrapom Dam

Bachelor of Technology: Electronics and Communication Engineering Maulana Abul Kalam Azad University of Technology

Material Science, Advanced Technologies, Metals, Clean Technologies

Samudrapom Dam is a freelance scientific and business writer based in Kolkata, India. He has been writing articles related to business and scientific topics for more than one and a half years. He has extensive experience in writing about advanced technologies, information technology, machinery, metals and metal products, clean technologies, finance and banking, automotive, household products, and the aerospace industry. He is passionate about the latest developments in advanced technologies, the ways these developments can be implemented in a real-world situation, and how these developments can positively impact common people.

Samudrapom also writes about the significance of different technologies for modern businesses, such as how the implementation of technology can improve a business process or streamline the entire business operation of an enterprise. He completed his Bachelor of Technology in Electronics and Communication Engineering in 2018 from Maulana Abul Kalam Azad University of Technology (MAKAUT). He is an avid reader and enjoys playing chess.

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Articles from Samudrapom

What is a Chatbot?

This article provides insights into the fundamental concepts, types, design, development, and applications of chatbot technology. Covering topics from early algorithms like AIML to modern natural language processing techniques, the article explores the diverse landscape of chatbots, from open and closed domains to rule-based and generative models. It concludes by speculating on the promising future of chatbots, anticipating their evolution into handling more intricate tasks and further integration into customer service and e-commerce.

20 Dec 2023

Transforming Telemedicine Using AI

This article explores the growing significance of artificial intelligence (AI) in telemedicine, addressing the integration of AI into the management of renal, neurological, gastrointestinal, and cardiac diseases. It discusses the importance of AI in telemedicine, emphasizing its role in overcoming implementation challenges and enhancing various aspects of healthcare, from remote monitoring and diagnosis to personalized treatment plans.

20 Dec 2023

Advancing Fire Safety: A Digital Twin-Based Framework for Smart Buildings

This study introduces a Digital Twin (DT)-centered Fire Safety Management (FSM) framework for smart buildings. Harnessing technologies like AI, IoT, AR, and BIM, the framework enhances decision-making, real-time information access, and FSM efficiency. Evaluation by Facility Management professionals affirms its effectiveness, with a majority expressing confidence in its clarity, data security, and utility for fire evacuation planning and Fire Safety Equipment (FSE) maintenance.

19 Dec 2023

Swin-APT: Enhancing Semantic Segmentation in Intelligent Transportation Systems

Researchers introduced Swin-APT, a deep learning-based model for semantic segmentation and object detection in Intelligent Transportation Systems (ITSs). The model, incorporating a Swin-Transformer-based lightweight network and a multiscale adapter network, demonstrated superior performance in road segmentation and marking detection tasks, outperforming existing models on various datasets, including achieving a remarkable 91.2% mIoU on the BDD100K dataset.

18 Dec 2023

Improved Deep Reinforcement Learning for Collision-Free Routing in Vehicular Ad-Hoc Networks

Researchers propose an Improved Deep Reinforcement Learning (IDRL) approach to optimize routing paths and reduce control overhead in Vehicular Ad-Hoc Networks (VANETs). The IDRL routing technique leverages deep reinforcement learning to dynamically determine routes based on transmission capacity and vehicular data, resulting in reduced latency, improved data reliability, and increased packet delivery ratio (PDR) compared to existing routing techniques.

15 Dec 2023

Double Camouflage Encryption of QR Codes for Secure UAV Landing

This paper introduces a double camouflage encryption method for QR codes in UAV landing scenarios to ensure information security. Utilizing a private key and carrier image, the QR code undergoes double camouflage encryption, modulating a public key based on ghost imaging principles to generate ciphertext. The decryption process involves extracting the camouflage image with the public key and decrypting the QR code with the private key.

14 Dec 2023

Real-time UAV Patrolling Video Positioning: Enhanced Algorithms Using DOM Rectification

Researchers present innovative visual positioning algorithms for unmanned aerial vehicle (UAV) patrolling video sequences. Utilizing a digital orthophoto map (DOM) rectification approach, the proposed model combines a precise polynomial-rectifying algorithm and a robust block-matching algorithm, demonstrating real-time UAV video positioning with high accuracy across diverse terrains and lighting conditions. Practical experiments validate the effectiveness of the algorithms, highlighting their speed, feasibility, and substantial improvement in accuracy, particularly when leveraging high-resolution region-DOMs.

13 Dec 2023

Real-world Robot Control Enhanced: Self-Attention Mechanism in Online Model Updates

Researchers propose an online model update algorithm utilizing a self-attention mechanism embedded in neural networks for risk-sensitive robot control. The study introduces a novel approach with four neural networks, addressing dynamics and kinematics models, and employs self-attention layers to detect abnormalities and perturbations in real-world robotic systems.

12 Dec 2023

The Role of AI in Robotic Process Automation

This article explores the transformative synergy of artificial intelligence (AI) with robotic process automation (RPA) in streamlining business tasks. It delves into the significance of AI in RPA, outlines a strategic RPA + AI implementation approach, and showcases practical applications in internal audit and invoice processing. The discussion also covers recent advancements, including a pioneering project (AIRPA) addressing challenges in AI-RPA integration for enhanced efficiency.

11 Dec 2023

IoT and ML for Behavioral Analysis of Ornamental Fish

Researchers proposed an IoT and ML-based approach to analyze ornamental goldfish behavior in response to environmental changes, particularly real-time water temperature and dissolved oxygen concentration. Utilizing IoT sensors and machine learning classifiers like Decision Tree, Naïve Bayes, Linear Discriminant Analysis, and K-Nearest Neighbor, the study demonstrated the effectiveness of the Decision Tree classifier in accurately classifying behavioral changes.

10 Dec 2023