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This paper proposes a hybrid system comprising multiple unmanned aerial vehicles (UAVs) to monitor nature. The proposed tributary mapping system consists of perception and control systems. A perception system is established for tributary mapping using three-dimensional light detection and ranging (LiDAR) semantic segmentation for surface water recognition. The system defines a water point cloud and segments the surface water area using singular value decomposition, applying the water-absorbing property of LiDAR. A path is generated through random sample consensus by calculating the center point from the segmented area. Each UAV is modeled using a continuous-time dynamic-based low-level model and a discrete event-time dynamic-based high-level model to control the multiple UAVs system. The desired plant behavior is designed considering the control objectives of the plant, and a supervisory controller is developed accordingly. A physics-based robot simulator is employed to verify the proposed tributary mapping system in perception and path generation and the performance of the hybrid system-based supervisory controller.

ASHRAE RP-1747 is a CO 2 -based demand-controlled ventilation (DCV) approach which uses trim and respond logic to dynamically adjust variable air volume (VAV) terminal units' minimum airflow setpoints based on zones' ventilation requirements. While simulation results and laboratory testing have estimated the impact on heating, ventilation, and air conditioning (HVAC) systems compared to traditional ventilation, there have been limited applications of RP-1747 in occupied, real-world buildings to date. This paper introduces a real-world implementation of RP-1747 DCV in an institutional office building over an eight-month period, using a supervisory control approach. During this implementation, a complementary temperature setback approach was also developed and employed in the case study building. These changes to the sequences of operation, as well as corrections to other sub-optimal sequences of operation discovered during implementation, resulted in a 36 ± 2 % and 2 ± 6 % reduction in heating and cooling energy use, respectively, while improving per person ventilation rates in the case study. The results aim to contribute to the body of literature on this emerging DCV approach and provide anecdotal evidence of its benefits and interactions with other control logic in a real-world application, while also demonstrating the benefits of supervisory control when implementing complex process control functions. [ABSTRACT FROM AUTHOR]