AI.rbo is an AI-driven, GIS-based system for monitoring mosquito-borne diseases. It predicts future outbreaks and supports clinical decisions in disease management. The technology covers diseases like Zika and Chikungunya. The dengue dashboard offers features for outbreak surveillance, including descriptive analytics and geocoded maps showing case distribution and past outbreaks. It also includes a predictive model using Machine Learning to forecast future outbreaks, aiding proactive planning. Using REDINT, it collects additional data for accurate forecasting. Clients can use forecast outputs to plan prevention and intervention efforts efficiently, saving costs and resources.
Health Industry
AI.rbo offers advanced arbovirus surveillance with AI-powered capabilities, covering not only dengue but also Zika and Chikungunya. It provides a comprehensive solution to monitor, predict, and manage mosquito-borne disease outbreaks.
The system's predictive algorithm leverages machine learning to forecast future outbreaks, empowering healthcare professionals and authorities with the ability to plan and allocate resources proactively. This helps in preventing and mitigating outbreaks effectively.
The Remote Data Input Interface (REDINT) enhances data collection by incorporating geocoding, weather information, landmarks, and socioeconomic data. This enriched data helps calculate outbreaks and predict future ones more accurately.
Clients can leverage the system's forecasted outputs to develop targeted prevention and intervention strategies. This precision allows for more efficient allocation of resources and cost-effective measures, ultimately reducing the impact of outbreaks.
AI.rbo offers customisable solutions to cater to the specific needs of different regions and healthcare systems. The customisable features allow clients to adapt the system to their unique requirements, ensuring that it can effectively address diverse challenges in arbovirus management.