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4 articles for “Black Box”

• Published Subscription 20 Nov 2024

  Automatic Vehicle Accident Detection and Reporting with a Blackbox

  By Nidhi Nityanand Bharati, Aditya Gajanan Joshi, Harshad Dashrath Joshi, Niraj Dipak Patil, Pradnya S. Narnaware

  Abstract: The development and deployment of digital driving technology for a semi-autonomous vehicle is the main goal of this project. Enhancing the driver-vehicle interaction and adding black box functionality are the objectives. The system utilizes an Arduino-based data acquisition system, converting analog control data to digital format and displaying it on an LCD. Communication occurs via embedded networking using the CAN protocol, ensuring efficient data transfer. The system also collects feedback …

  Published in International Journal of Analog Integrated Circuits · Vol. 10, Issue 2, 2024 · pp. 21–30 Read article →

• Published Subscription 18 Nov 2024

  Comprehensive Systems Review for Accident Detection, Prevention, and Real-Time Alerting Mechanisms

  By Khelan Vaishnav, Rudra Joshi, Parul H Panchal

  Abstract: The growth of technology and infrastructure at a rapid pace has made our lives easier. The increased frequency of road accidents and possible traffic dangers brought about by newer technologies has resulted in a significant loss of life and property due to inadequate emergency facilities and preventive measures. The greatest hazard to human life is traffic accidents. High speeds combined with intoxication are the main causes of many accidents. Vehicle …

  Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–4 Read article →

• Published Subscription 1 Sep 2026

  Exploration of Explainable Artificial Intelligence (XAI) Techniques to Enhance Model Interpretability

  By Avnish soni, Vivek Kumar Verma, Ayushi Singh, Pavitr Jain, Sharmishtha Gupta, Arnav Dubey

  Abstract: Explainable Artificial Intelligence (XAI) has become a major research field because of the rising application of complex machine learning and deep learning models in actual decision-making systems. Although such models are accurate, they are in many cases black boxes and therefore the users do not have much understanding of the way the decisions are generated. This absence of transparency brings up some serious concerns connected with trust, accountability, fairness, and …

  Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article →

• Published Subscription 5 Jul 2023

  Unlocking the Potential: Machine Learning Driven Explainable AI Applications Across Diverse Domains

  By Mritunjay Kumar Ranjan, Kushal Roy, Anushka Mahind, Devashish Bhavsar, Somesh Nemade, Arif Md. Sattar

  Abstract: Explainable artificial intelligence (XAI) aims to make discoveries and output generated by machine learning algorithms accessible to human users in a trustworthy and easy-to-understand manner. It describes the impact of an AI model and any potential biases, helping in characterizing models with accuracy, fairness, transparency, and outcomes in decision-making powered by AI. XAI focuses on understanding the data used to train the model, its predictions, the specific elements involved in …

  Published in International Journal of Software Computing and Testing · Vol. 9, Issue 1, 2023 · pp. 24–32 Read article →