Safety Threat Detection in Construction Zones using Dense YOLOv8 with White Shark Nested Attention Network Rajeeth T J, Chitaranjan Dalai, Vanitha G Naik, Vipul Vekariya, Kannadasan B, et al. 8th International Conference on I Smac Iot in Social Mobile Analytics and Cloud I Smac 2024 Proceedings, 2024 The construction industry faces numerous hazards and risks, many of which remain unmonitored, leading to accidents and injuries. To address these challenges and improve safety in construction areas, this paper proposes a novel approach based on the Dense YOLOv8 White Shark Nested Attention Network (DYWS-NAN) for safety threat detection. Utilizing the Construction Site Safety Image Dataset, which contains a wide range of images depicting safety compliance and violations, the proposed method ensures precise identification of safety threats. The dataset undergoes rigorous pre-processing using the Grid-Constrained Data Cleansing Method to remove noise and enhance image quality, enabling the model to focus on critical safety features. Following pre-processing, feature extraction and classification are performed using the DYWS-NAN architecture, which combines YOLOv8's real-time object detection capabilities with the White Shark Nested Attention mechanism. This integration enhances both object feature extraction and classification performance, significantly improving safety threat detection accuracy. Simulations conducted in the Python environment demonstrate an accuracy level of 99.4%, highlighting the method's effectiveness in reducing false alarms and enabling timely safety interventions in construction zones. This approach enhances safety management and ensures better compliance with safety regulations.
Efficient complexity based adaptive system for cloud resources Sarvesh Kumar, Dyagala Naga Sudha, Anupama Anupama, B. Kannadasan, Ajay Singh Yadav, et al. Journal of Interdisciplinary Mathematics, 2023 Cloud computing is a new IT concept, that is no longer solely applicable to the economic system however as nicely very beneficial in science. The issue of asset distribution and income expansion is likewise similarly significant, particularly about cloud security. This achieves the need of various displaying strategies including however not restricted, to security danger, asset assignment, and income boost models. These offerings are billed on a utilization basis. The cloud services are provided by the CSPs to the end users in an optimized way by using our mathematical proposed algorithm. This proposed algorithm is simulated in the cloud simulator. It prompts financially savvy arrangements by lessening the execution season of enormous application testing. As a piece of framework assets, cloud testing can accomplish its productivity by dealing with the boundaries like organization traffic, Circle Stockpiling, and Smash speed. In this paper, we propose another fluffy numerical model to accomplish a superior degree for the above boundaries. The results of the outcomes informs that the proposed algorithm CROS (Cloud Resource Optimized System) performances are better.
Smart Transport System for Passenger Comfort using IoT Awari Mahesh Babu, T. Thulasimani, D. Sundaranarayana, B. Kannadasan, R. Salini, et al. Mysurucon 2022 2022 IEEE 2nd Mysore Sub Section International Conference, 2022
I have vast of strong industry experience in Geographic Information Systems (GIS), Remote Sensing, Spatial Data Modelling, and Geospatial Consulting, working across India, USA, and Indonesia. My work involved developing high-quality geospatial datasets, handling large-volume imagery, and delivering accurate spatial solutions for government agencies, utility companies, environmental firms, and global consulting organizations.
