Artificial Intelligence Based COVID-19 Informative Chatbot
Outbound telephonic hotline for COVID-19 awareness in Urdu language
For the last 4 years, Dr. M. Ali Tahir, Dr. Adnan Ul Hasan, and team members have been working on different industrial projects related to speech technology. These projects include “Urdu TV broadcast analytics using speech recognition and computer vision”, “Urdu voice-enabled vehicle navigation using speech recognition” and “Telephone call surveillance and analytics using speech recognition”. Using their expertise they are developing an automatic telephonic system that calls up thousands of random people daily, asks them Urdu questions about their health conditions, and provides awareness about COVID-19. The system is completely automatic requiring no human operators, and its use of Urdu language enables us to reach the masses in Pakistan. The data collected by this system can be used by the government for statistics about Covid-19’s prevalence, identifying virus hotspots, patterns of disease proliferation, and plasma donors.
Through this system, we can access the largest segment of Pakistani population, including less literate people because of Urdu language and voice-based operation. This system can later be used for purposes other than Corona, e.g. rural healthcare, government information dissemination, and advertisement.
Artificial Intelligence Based Insights about COVID-19
We have developed several machine learning models for making predictions on various real-world problems. Our lab has recently completed a project (Sep 2017 – Aug 2019) funded by the Pakistan Science Foundation titled “Artificial Intelligence-based Diagnostic Screening for Dengue Fever”. Since the forecasting and analysis of COVID-19 require the same domain expertise with fundamental knowledge of Machine Learning and simulation models, the skills of the technical team that worked on the aforementioned project and the algorithms developed are being utilized again. Data is being gathered from several sources like publicly available pandemic spread data, data from local hospitals and health institutions. Deep learning based forecasting and prediction algorithms are being trained on the collected data.
The project is currently being run using volunteer time dedicated by different students, researchers, and postdocs under the leadership of Prof. Dr. Faisal Shafait. Stay tuned for data driven insights about COVID-19!
The spread of coronavirus in over 200 countries within a span of a few months necessitates the development of forecasting models that can assist governments around the globe in keeping an eye on their country’s situation forecast so that preventive measures can be timely taken. Since the epidemic spread is still in the early stages in some countries, forecasting models harnessing data from countries already hit by the epidemic will provide a realistic and timely intimation of risks of potential outbreaks in these countries. The proposed open-source data and machine learning model will provide useful insights into the disease spread spectrum, diagnostics, and prevention strategies. Data scientists around the world will be encouraged to pool in their efforts and augment our model to assist the governmental entities in taking emergency response measures ahead of time during a pandemic outbreak.
Our forecasting model is based on a custom architecture of Deep Long Short-Term Memory (LSTM) Neural Networks and is capable of using transfer learning to adapt the model based on limited availability of real-world data.
