VIVOTEK Deploys AI Monitoring System to Protect Taiwan’s Zhonggua River
VIVOTEK has deployed an AI based ecological monitoring system along Taiwan’s Zhonggua River, announced in a press release. The project was carried out in partnership with National Chung Hsing University and AI startup DATAYOO to support biodiversity research and river conservation.
The system uses high resolution PTZ cameras connected to VIVOTEK’s VORTEX cloud surveillance platform. It enables continuous observation of wildlife and environmental conditions without requiring researchers to enter sensitive habitats. The cameras record species such as the crab eating mongoose, kingfishers, spot billed ducks, turtles, and wild boars, contributing to a growing biodiversity database.
Beyond wildlife monitoring, the system tracks water levels and conditions to help manage flood risks during typhoons and heavy rainfall. It also assists in identifying pollution sources and assessing ecological impacts after contamination events.
Footage collected from the monitoring network is being used in environmental education initiatives and community programs. According to the press release, the deployment has improved the efficiency of biodiversity monitoring and enhanced disaster management and environmental protection capabilities in the Zhonggua River region.
We hope you enjoyed this article.
Consider subscribing to one of our newsletters like Enterprise AI Brief, Industrial AI Weekly or Daily AI Brief.
Also, consider following us on social media:
More from: Enterprise
Subscribe to Industrial AI Weekly
The latest advancements in smart manufacturing, predictive maintenance, AI-driven quality control, supply chain & more.
Market report
2025 State of Data Security Report: Quantifying AI’s Impact on Data Risk
The 2025 State of Data Security Report by Varonis analyzes the impact of AI on data security across 1,000 IT environments. It highlights critical vulnerabilities such as exposed sensitive cloud data, ghost users, and unsanctioned AI applications. The report emphasizes the need for robust data governance and security measures to mitigate AI-related risks.
Read more