AI Powered Adaptive Assessment

This project focuses on the problem of time and the human resources involved in conducting a secure offline/online pre-recruitment or training assessment. We are proposing an online secured platform powered by Artificial Intelligence and Machine Learning for safe and smooth online assessments, boasting of an advanced reporting and automated process to save time and ensure the right decisions are made regarding employee performance.

Retail Supply Chain Predictive Analytics

The project aims predict the demand of customers for small and medium size businesses. Forecasting models will be developed analyze historical data to understand patterns and correlations. Machine learning will be applied to determine how the accuracy can be improved over existing statistical methods, such as Fourier Regression Analysis which is commonly used in retail demand chain management. The demand forecasting model will examine customer behavior and the context surrounding that behavior, including upcoming holidays, the weather, or a recent event such as COVID-19.

Investigating the use of mixed reality technologies as a solution to help mitigate the challenges under the COVID-19 restrictions for artistic collaboration and education

Traditionally, artistic communities relied on face-to-face encounters to learn their skills, collaborate, and showcase their work. Due to COVID-19, performances in the arts have been abruptly halted and traditional music lessons take place at a studio has stopped.
This project aims to examine and provide a prototype solution to mitigate the challenges in artistic collaboration and education that are the result of the COVID-19 pandemic.

Biogeographical modeling of coronavirus dispersal

The project will reformulate the coronavirus dispersal hypothesis to food web disturbance caused by ‘social mood’ of human behaviors. We will develop a dynamic system-theoretic model to capture the change pattern of such a “social mood” and identify early warning indictors. The approach will be an advance for understanding the pathogen dispersal risk among those known- and unknown- susceptible species along the food web. This will be very important for contingency plans of COVID-19, especially in travel recommendations and pathogen containment.

Data analysis and image processing for livestock identification

OneCup provides cattle management solutions to the livestock industry. Our AI is called BETSY - Bovine Expert Tracking and Surveillance. Using artificial intelligence, we put a rancher's skillset into a device the size of a small book. With several types of cameras, BETSY can ID and track cattle activity 24x7. For example, she can track an animal's growth over a season, or determine if an animal is suffering from a disease or lameness. When BETSY finds something that requires human intervention, she texts or emails a human immediately.

360 Live ID for Livestock

OneCup provides cattle management solutions to the livestock industry. Our AI is called BETSY - Bovine Expert Tracking and Surveillance. Using artificial intelligence, we put a rancher's skillset into a device the size of a small book. With several types of cameras, BETSY can ID and track cattle activity 24x7. For example, she can track an animal's growth over a season, or determine if an animal is suffering from a disease or lameness. When BETSY finds something that requires human intervention, she texts or emails a human immediately.

Intelligent Systems Data Ingestion and Analytics

This project will support the development of comprehensive, multidisciplinary Smart Building, Smart Transportation, and Smart City management systems in order to improve energy performance, operations cost, safety and reliability for large infrastructures in the private and public sector.
The research problem to be addressed is to develop effective methods to ingest and analyze massive amounts of streaming data from large numbers of WiFi-connected IoT devices monitoring buildings, vehicles, and transportation corridors within a Smart Campus or Smart City.

Radar-based Real-Time Detection of Overdose Incidents in Small Public Spaces

This project aims to train machine learning models that use millimetre-wave radar data to non-invasively detect health incidents, such as overdoses in public bathroom stalls.

Image segmentation of foliage and man-made objects in aerial RGB images

Unmanned Aerial Vehicle (UAV) technology has advanced significantly in recent years. With the aerial data, analysis provides solutions to government agencies and industries, including the energy and forestry sectors, as well as urban/rural planning. Among the many aerial data modalities, RGB images play an important role in the analytics process. Our research problem involves segmenting aerial RGB images composed of natural and man-made objects into two categories in real-time as the data, i.e., video frames, are collected.

Neurorehabilitation of the hand post-stroke or brain injury

Stroke is the number one cause of adult disability in the world. Due to the neurological damage from stroke, a vast majority of individuals suffer from hand function disability (~70%). To improve hand function and overcome challenges from this disability, IRegained has developed the MyHandTM system, a connected mechatronic device with programmed proprietary hand function training protocols developed through deep research in neuroplasticity for targeted hand function therapy.

Pages