Research Themes

  • Smart and Sustainable Agriculture
  • Digital twining and 3D point cloud scanning
  • Predictive Maintenance in Industry
  • AIoT for Smart healthcare and personalized patient decision

Current Projects

Project 1: Wireless Sensor Network for Greenhouse Monitoring Using LoRaWAN
 
Objective: The purpose of this project is to design and develop a wireless sensor network for greenhouse environments using LoRaWAN technology. The system collects real-time environmental data such as temperature, humidity, soil moisture, and light intensity to enable efficient monitoring and decision-making. By leveraging long-range, low-power communication, the project aims to improve resource utilization, support precision agriculture practices, and enhance crop productivity.
 
Partner: Research
 
Project 2: Intelligent Compost Monitoring System
 
Objective: The purpose of this project is to develop an IoT-based compost monitoring system that continuously tracks critical parameters involved in the composting process, including temperature, moisture, and other environmental conditions. The collected data is analyzed to optimize compost quality, improve process efficiency, and provide timely insights for sustainable waste management practices.
 
Partner: Research
 
Project 3: Cannabis Yield Prediction System Using Artificial Intelligence
 
Objective: The purpose of this project is to investigate the use of artificial intelligence and data analytics techniques to predict cannabis yield based on environmental conditions, cultivation practices, and historical growth data. The system aims to assist growers in making informed decisions, optimizing production strategies, and improving yield consistency and overall crop performance.
 
Partner: Research

 

Project 4: GI Sense: Intelligent Ingestible Diagnostics for Gastrointestinal Health Monitoring

Objective: To develop next-generation ingestible smart capsule technologies capable of monitoring gastrointestinal (GI) motility and physiological activity in a non-invasive manner. The project combines biomedical sensing, embedded electronics, wireless communication, artificial intelligence, and digital health technologies to improve the diagnosis and management of gastrointestinal disorders.

Partner: Research

 

 

Previous Projects

Project 1: Leveraging Data Analytics to Measure Elevator Car Performance

Objective: The purpose of this project is to design an advanced elevator monitoring system that leverages artificial intelligence (AI), IoT sensors, and data analytics to track elevator usage, detect operational incidents, and predict maintenance needs.

Partner: Industry

Project 2: Using machine learning to detect assets within 3D depth scans

Objective: The purpose of this project is to investigate and improve edge detection, object detection, and object identification algorithms for efficient and accurate automated asset management in industrial plants such as refineries and petrochemical plants. This will result in Antea’s ability to expand its services to the industrial sector.

Partner: Industry

Project 3: Bringing Bins to Life

Objective: The issue surrounding the litter problem is societal, long-standing, ongoing, and difficult to combat. litter negatively affects the environment, people’s health, and the local economy, and has numerous ripple effects within each. The purpose of this project is to develop a smart bin system that prompts a response in preventing littering behaviors; and reward or recognize ideal litter management behaviors.

Partner: Academic, City

 

 

 

Publications

  • List of papers, journals, and articles with download links