Summary of Big Data and Deep Learning in Smart Cities: a Comprehensive Dataset For Ai-driven Traffic Accident Detection and Computer Vision Systems, by Victor Adewopo et al.
Big Data and Deep Learning in Smart Cities: A Comprehensive Dataset for AI-Driven Traffic Accident Detection and Computer Vision Systems
by Victor Adewopo, Nelly Elsayed, Zag Elsayed, Murat Ozer, Constantinos Zekios, Ahmed Abdelgawad, Magdy Bayoumi
First submitted to arxiv on: 7 Jan 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel comprehensive dataset is introduced for traffic accident detection in smart cities, leveraging state-of-the-art algorithms tailored for action recognition in video sequences. The dataset combines data from various sources, including road networks, weather conditions, and regions worldwide. This research aims to bridge existing gaps by providing benchmark datasets that can advance academic research and real-time accident detection applications, contributing to the evolution of smart urban environments. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary In a world where cars and pedestrians are always on the move, it’s crucial to make cities safer and more efficient. One way to do this is by using advanced technology to detect traffic accidents before they happen. This study creates a new dataset that helps computers recognize actions in videos and track objects like people. The dataset includes information from many different places around the world, so it can be used to train machines to detect accidents in various conditions. By improving our understanding of how technology can make cities safer, this research aims to contribute to a better quality of life for city dwellers. |
