Abstract: A rope anchor with a J-shaped a body having a hook and spine. The end of the spine has an attachment hole for a rope and an elongated, teardrop-shaped rope slot that is either enclosed or gated. The gate is biased closed to span the open side of the rope slot and pushed opened to allow access for a rope. A tip, composed of a flat chip of metallic material, fits into a slot at the end of the hook. The tip is generally triangular with two or three sharp corners, or square or rectangular with four sharp corners. The slot orients the tip so that only one of the sharp corners is exposed, or so that two adjacent sharp corners are exposed. When an exposed sharp corner is not suitable for use, the tip can be reoriented to expose a different sharp corner.

Abstract: A rope anchor with a J-shaped a body having a hook and spine. The end of the spine has an attachment hole for a rope and an elongated, teardrop-shaped rope slot that is either enclosed or gated. The gate is biased closed to span the open side of the rope slot and pushed opened to allow access for a rope. A tip, composed of a flat chip of metallic material, fits into a slot at the end of the hook. The tip is generally triangular with two or three sharp corners, or square or rectangular with four sharp corners. The slot orients the tip so that only one of the sharp corners is exposed, or so that two adjacent sharp corners are exposed. When an exposed sharp corner is not suitable for use, the tip can be reoriented to expose a different sharp corner.

Abstract: A method of controlling the heating, ventilation and air conditioning (HVAC) system of a building, the method comprising the steps of: (a) developing an initial thermal model of the building, and continuously updating the thermal model over time; (b) utilising the thermal model to continuously develop a daily HVAC operating plan for the building; and (c) continuously examining a current HVAC operating plan and optimising the alignment of the current HVAC operation with the current HVAC operating plan.

Abstract: A method of controlling the heating, ventilation and air conditioning (HVAC) system of a building, the method comprising the steps of: (a) developing an initial thermal model of the building, and continuously updating the thermal model over time; (b) utilising the thermal model to continuously develop a daily HVAC operating plan for the building; and (c) continuously examining a current HVAC operating plan and optimising the alignment of the current HVAC operation with the current HVAC operating plan.

Abstract: A method for detecting faulty operation of a multi-variable system is described. The method includes receiving operational data from a plurality of components of the multi-variable system and processing the operational data in accordance with a plurality of dynamic machine learning fault detection models to generate a plurality of fault detection results. Each fault detection model uses a plurality of variables to model one or more components of the multi-variable system and is adapted to detect normal or faulty operation of an associated component or set of components of the multi-variable system. The plurality of fault detection results are output.

Abstract: A method of controlling the heating, ventilation and air conditioning (HVAC) system of a building, the method comprising the steps of: (a) developing an initial thermal model of the building, and continuously updating the thermal model over time; (b) utilising the thermal model to continuously develop a daily HVAC operating plan for the building; and (c) continuously examining a current HVAC operating plan and optimising the alignment of the current HVAC operation with the current HVAC operating plan.

Abstract: A method for detecting faulty operation of a multi-variable system is described. The method includes receiving operational data from a plurality of components of the multi-variable system and processing the operational data in accordance with a plurality of dynamic machine learning fault detection models to generate a plurality of fault detection results. Each fault detection model uses a plurality of variables to model one or more components of the multi-variable system and is adapted to detect normal or faulty operation of an associated component or set of components of the multi-variable system. The plurality of fault detection results are output.