The goal of this project is to develop an intelligent system that can autonomously navigate in Campus building spaces, limited to open spaces. The experiments for this project will be limited to the following spaces: Room 2017, Civil Engineering Hydrosystems Laboratory Building. This project will also collect data on the indoor environmental conditions (e.g, temperature, humidity, lighting levels) using multi-model sensors, and also recommend indoors environmental settings for energy savings and increased occupant comfort. The mobile unit will be integrated with the following components:

1. Sensors (mounted on the robotic unit) to read indoor physical parameters (temperature, humidity, lighting levels, CO2)

2. Charging station to periodically charge the unit.

3. CPU to command and manage 

4. Autonomous navigation which includes mapping, collision avoidance, and adaptive navigation (learning the sensing locations for accurate energy prediction. 

5. Data collection and communication which includes the collection of indoor physical parameters (using the mounted sensors) and connection to a database. 

6. Optimization, which includes algorithms for predicting the energy consumption based on indoor conditions, weather conditions, and time od the day. It also predicts the occupant thermal comfort states based on occupant data and indoor condition. Lastly, it recommends indoor condition settings that balance energy savings and occupant thermal comfort.

This unit will also be integrated with a vertical stick with a height equivalent to the eye-level height and a sound system that "beeps" in proximity to its occupants.