A network of wireless remote climate sensors in a heating, ventilation, and air conditioning (HVAC) system permits the creation of personalized microclimates within an enclosed space. In addition to collecting temperature and humidity data, the wireless remote climate sensors can detect whether the enclosed space is occupied by a human. Human detection is made possible by optional cameras, microphones, and gas sensors on the wireless remote climate sensors. As the human moves throughout the enclosed space, the HVAC system is able to track the human's movement using the wireless remote climate sensors. The HVAC system may adjust airflow to different portions of the enclosed space based on the human's location. The result is an efficient use of system resources to keep users at their ideal temperature.

A network of wireless remote climate sensors in a heating, ventilation, and air conditioning (HVAC) system permits the creation of personalized microclimates within an enclosed space. In addition to collecting temperature and humidity data, the wireless remote climate sensors can detect whether the enclosed space is occupied by a human. Human detection is made possible by optional cameras, microphones, and gas sensors on the wireless remote climate sensors. As the human moves throughout the enclosed space, the HVAC system is able to track the human's movement using the wireless remote climate sensors. The HVAC system may adjust airflow to different portions of the enclosed space based on the human's location. The result is an efficient use of system resources to keep users at their ideal temperature.

Heating and cooling systems at various geographical locations are controlled by a central energy management service unit to maintain comfortable indoor temperatures. In some weather conditions, people may intuitively prefer a slightly warmer or cooler indoor temperature. In systems equipped with environmental learning capabilities, an apparent outdoor temperature is determined based on the geographic location itself, the season at the geographic location, the forecasted actual temperature, and one or more seasonal weather factors such as wind velocity or humidity. The apparent temperature and a trained machine learning system are used to select an automated schedule for the geographic location to be directly transmitted to devices at the location. The automated schedule can vary from typical schedules by causing the heating and cooling systems to maintain a temperature that is slightly warmer or cooler than typical indoor temperatures.

Improved systems for heating and cooling a space may include a heating and cooling unit for providing heating and cooling functions mounted inside a housing assembly and a display unit mounted to the housing assembly. A control unit may be coupled to the heating and cooling unit and the display unit. The control unit may be operative to cause an image or video associated with heat be displayed on the display unit when the heating and cooling unit is in the heating mode of operation and to cause an image or video associated with coolness be displayed on the display unit when the heating and cooling unit is in the cooling mode of operation. The control unit may be coupled to a server that enables remotes operation of the system via a client application. Other implementations also may be provided.

A monitoring system for apparatus and systems in commercial and residential properties is provided. The monitoring system consists of a head unit and a tail unit, each of which has one or more sensors that measure performance parameters that are important to understanding the performance of the apparatus and system being monitored. As an example, an HVAC system may be monitored to determine when an air filter needs to be changed, or to predict when failure of the HVAC system may be imminent. The sensor array in the head unit and tail unit measure performance and report alerts and historical system performance to users through a mobile app, social media accounts, or any other system for communicating over a wired or wireless network connection.

There is described a system and method for configuring, commissioning and troubleshooting an HVAC unit. A unit type configuration is established based on a type of HVAC system and temperature data, humidity data, and/or indoor air quality data. A fan configuration is established based on whether a variable frequency drive fan is identified. Cooling and heating stage configurations are established based on a compressor parameter and a heating stage parameter. An available auxiliary termination is identified in response to establishing the configurations. A safety is assigned to the available auxiliary termination in response to identifying the available auxiliary termination. An IO table is provided to an HVAC controller, which includes physical input/output assignments for the terminations of the HVAC controller based on the configurations and the assigned safety. For another embodiment, the fan configuration is established based on one of a traditional stage blower fan or variable frequency drive fan.

The present disclosure relates to a heating, ventilation, and air conditioning (HVAC) system including a sensor system configured to detect heat indications within a plurality of areas of a conditioned space, wherein the sensor system comprise a thermal light detector, and a controller configured to receive feedback from the sensor system and, based on the feedback, control airflow distribution, via an airflow distribution system, such that airflow management for each of the plurality of areas is individually correlated to a heat indication detected for the respective area.

A visible light sensor may be configured to sense environmental characteristics of a space using an image of the space. The visible light sensor may be controlled in one or more modes, including a daylight glare sensor mode, a daylighting sensor mode, a color sensor mode, and/or an occupancy/vacancy sensor mode. In the daylight glare sensor mode, the visible light sensor may be configured to decrease or eliminate glare within a space. In the daylighting sensor mode and the color sensor mode, the visible light sensor may be configured to provide a preferred amount of light and color temperature, respectively, within the space. In the occupancy/vacancy sensor mode, the visible light sensor may be configured to detect an occupancy/vacancy condition within the space and adjust one or more control devices according to the occupation or vacancy of the space. The visible light sensor may be configured to protect the privacy of users within the space via software, a removable module, and/or a special sensor.

A method of controlling signal transmission in a building control system including measuring a number of signal values associated with an environmental variable using a sensor of a wireless device, dynamically determining, by the wireless device, a noise threshold based on the number of signal values, combining a first signal value and a second signal value of the number of signal values using a mathematical relationship to determine a result associated with the first signal value and the second signal value, and periodically transmitting the first signal value from the wireless measurement device to a controller in response to the result exceeding the noise threshold.

A method and computing device for inferring an airflow of a controlled appliance operating in an area of a building. The computing device stores a predictive model. The computing device determines a measured airflow of the controlled appliance and a plurality of consecutive temperature measurements in the area. The computing device executes a neural network inference engine using the predictive model for inferring an inferred airflow based on inputs. The inputs comprise the measured airflow and the plurality of consecutive temperature measurements. The inputs may further include at least one of a plurality of consecutive humidity level measurements in the area and a plurality of consecutive carbon dioxide (CO2) level measurements in the area. For instance, the controlled appliance is a Variable Air Volume (VAV) appliance and a K factor of the VAV appliance is calculated based on the inferred airflow.