Weather Based Thermostat Control for HVAC Systems

Adapting heating mode to individual comfort needs through machine learning-based predictive modeling. The system analyzes real-time temperature, humidity, and wind data to predict weather patterns, then adjusts heating parameters to maintain optimal indoor conditions. The predictive model incorporates advanced statistical techniques, including ARIMA and LSTM networks, to capture complex relationships between environmental factors and human comfort responses. This enables personalized heating strategies that dynamically adapt to changing weather conditions, ensuring optimal indoor comfort while minimizing energy consumption.

Source

HVAC system optimization using weather forecasting enables proactive control of indoor climate conditions. The system analyzes future weather patterns and adjusts HVAC operation in real-time to maintain optimal indoor conditions. This predictive approach enables the system to anticipate and respond to temperature and humidity fluctuations, thereby improving energy efficiency and indoor air quality. The system integrates weather data with traditional HVAC controls to dynamically adjust fan speeds, blower operation, and refrigerant flow, ensuring optimal indoor climate conditions while minimizing energy consumption.

Source

Air conditioning system that dynamically adjusts indoor temperature based on solar radiation levels. The system monitors both solar radiation and room temperature to determine the optimal indoor temperature. When solar radiation exceeds a predetermined threshold, the system automatically sets the room temperature to a reference value. However, if the room temperature exceeds this reference, the system adjusts the temperature threshold to prevent excessive heating. This approach enables precise temperature control even in high-sunlight environments, while preventing overheating.

Source

Real-time weather control for air conditioning systems that enables users to receive personalized weather alerts and instructions directly on the control panel. The system utilizes a communication link to receive weather forecasts and intensity data, then dynamically displays relevant weather conditions and alerts on the control panel. This enables users to receive weather-specific information and instructions without relying on separate environmental monitoring devices. The system can switch between weather conditions and intensity levels based on the user's preferences, providing a more intuitive and proactive approach to weather management.

Source

Smart thermostat that can control the ambient temperature in one area when the thermostat is located in a different area. The thermostat uses setpoint modification factors to adjust the desired temperature based on factors like time of day, season, location, and weather conditions. This allows the thermostat to better regulate the temperature in the controlled area even when it's located in a different area.

Source

Smart air conditioning control method and system that uses artificial intelligence to optimize energy consumption and indoor comfort of air conditioning systems. The method involves using a deep learning model to predict future outdoor temperatures and humidity, then adjusting the indoor temperature setpoint based on the predictions to balance energy savings and comfort. The model learns over time to make better adjustments. The system collects indoor and outdoor environment data from sensors, runs the predictions through the model, and updates the model based on the resulting energy consumption and comfort levels.

Source

Smart thermostat with enhanced features to reduce energy usage, improve user comfort, and provide home monitoring. The thermostat has advanced capabilities like dynamic energy optimization based on real-time rates, demand response, and comfort balancing. It also has presence detection using sensors and devices to automatically arm/disarm the system when authorized users are present. The thermostat communicates with remote servers for rate plans and demand response signals.

Source

Air-conditioned ventilation system that automatically adjusts indoor temperature without manual operation. The system integrates weather forecasting data with location-based control, enabling precise temperature regulation based on real-time weather conditions. The system continuously monitors indoor temperature and adjusts ventilation rates accordingly, eliminating the need for manual operation or scheduling.

Source

Air conditioning control method and device that enables dynamic adaptation to weather conditions through user-defined scene templates. The method employs a user-configurable scene template system that allows users to define specific operating conditions for their air conditioning system. The system then dynamically adjusts the system's performance parameters to match these defined conditions, providing personalized comfort and energy efficiency.

Source

Regulating heating, cooling, and air conditioning systems based on weather forecasts to improve comfort and efficiency. The system integrates weather data into conventional temperature-based control by receiving forecast information through a dedicated receiver. This enables proactive adjustment of heating/cooling performance to anticipate temperature changes, maintaining optimal indoor conditions even before external temperature shifts occur.

Source

A weather forecast-based air conditioning system adjustment method that optimizes indoor temperature control in subway stations by predicting cooling demand through weather forecasts. The method involves collecting real-time indoor and outdoor temperature and humidity data, as well as forecasted weather conditions, to determine the required cooling load. By analyzing the forecasted cooling demand, the system adjusts its control strategy to achieve indoor temperature targets within a specified time frame, enabling more precise and efficient temperature control compared to traditional load-based control methods.

Source

Thermostat for controlling heating, ventilation, and air conditioning systems that automatically adjusts temperature settings based on environmental conditions. The thermostat incorporates sensors for temperature and humidity, and employs a dew point detection method to maintain optimal heating levels. The system automatically adjusts temperature settings when the dew point exceeds the setpoint, ensuring the air remains within the desired temperature range. This feature prevents overheating and condensation issues that can occur when heating systems are set too low.

Source

Predictive free cooling system for HVAC systems that optimizes energy savings through precise temperature control. The system employs advanced sensors and algorithms to monitor refrigerant flow and temperature dynamics, enabling accurate detection of optimal cooling periods. This predictive approach eliminates the need for manual intervention, reduces energy waste, and eliminates the need for frequent system updates and maintenance. The system integrates with existing building management systems (BMS) to automate the control sequence, ensuring continuous operation while maintaining precise temperature control.

Source

Indoor climate control system that integrates independent fresh air devices and HVAC through intelligent linkage control, enabling energy-efficient operation by dynamically coordinating heating and ventilation modes. The system features an integrated controller that monitors and regulates indoor air quality, temperature, and humidity while automatically controlling HVAC operation through intelligent linkage modes. The system incorporates sensors for air quality, carbon dioxide levels, and lighting conditions, enabling precise control of the indoor environment. The system achieves energy savings through optimized fresh air distribution and HVAC operation, while maintaining optimal indoor conditions.

Source

A system that automatically adjusts HVAC operation parameters based on real-time weather forecasts. The system maintains multiple control plans for different weather scenarios and automatically selects the most appropriate plan when deviations from the forecast occur. This enables real-time optimization of HVAC performance while maintaining energy efficiency. The system continuously monitors weather conditions and selects the best control plan from a predefined set, ensuring continuous operation of HVAC equipment even when forecast accuracy is compromised.

Source

A method and apparatus for optimizing heating system performance through adaptive predictive modeling. The system uses weather forecasts to determine optimal heating signals, incorporating specific building characteristics like insulation, window size, and orientation. By analyzing historical weather patterns and building-specific factors, the system dynamically adjusts heating parameters to achieve optimal energy efficiency. The method incorporates multiple weather parameters, including solar radiation, wind, and precipitation, and incorporates building-specific coefficients to account for unique thermal characteristics. The system continuously learns and adapts to changing weather conditions, enabling more precise heating control and improved energy savings.

Source

Intelligent temperature control system that optimizes room temperature based on real-time weather forecasts and historical data. The system integrates with location-based weather services to predict future temperature conditions, then adjusts room temperature settings in response. This enables proactive temperature management through both weather forecasting and past data analysis. The system also incorporates door and window opening detection, allowing precise temperature control during occupancy periods. The system can be integrated into various applications, including smart home systems and hotel room control systems.

Source

Air conditioner control method that combines meteorological parameters with air conditioning technology. The method analyzes weather patterns and temperature differences to predict future indoor temperature changes, then adjusts the air conditioner's operating parameters in advance to maintain optimal comfort. This approach enables proactive temperature control by anticipating changes in weather conditions before they occur, ensuring consistent indoor comfort levels throughout the day.

Source

Weather-linked air conditioning control method that enables adaptive temperature adjustments based on real-time weather conditions. The system integrates weather monitoring with air conditioning control, enabling precise temperature adjustments in response to changing weather conditions. The system comprises an air conditioner with a central processing unit, an operating parameters setting mechanism, and a weather information acquisition module. The operating parameters include temperature settings, which are initially set manually by the user. The weather information acquisition module continuously monitors weather conditions in the area where the air conditioner is located, providing real-time data to the central processing unit. This enables the air conditioner to automatically adjust its temperature settings in response to changes in the weather, ensuring optimal indoor comfort while maintaining energy efficiency.

Source

Air conditioner control method and device that dynamically adjusts operating parameters based on real-time environmental conditions. The method integrates weather data acquisition with the air conditioner's control logic, enabling intelligent temperature and humidity adjustments. The system employs time-based control strategies that adapt to changing environmental conditions, such as temperature fluctuations during the day and nighttime. This approach ensures optimal indoor comfort while minimizing manual intervention.

Source

Predictive free-cooling for HVAC systems optimizes energy consumption through automated monitoring and control. The system analyzes real-time weather data to determine optimal free-cooling conditions based on wet and dry bulb temperatures, enabling precise control of cooling operation. The system continuously monitors weather forecasts and plant conditions to determine when free-cooling can be safely implemented, eliminating the need for manual intervention. This predictive approach ensures efficient energy savings while maintaining reliable cooling operation.

Source

Air conditioner with adaptive cooling control that optimizes operation based on weather patterns. The system integrates weather sensors for atmospheric pressure, temperature, and humidity, as well as time-of-day indicators, to predict and respond to changes in the weather environment. It maintains a set temperature target while dynamically adjusting to changes in weather conditions, such as transitions from sunny to rainy days or nighttime to daytime patterns. This adaptive control approach enables the air conditioner to maintain optimal indoor conditions while minimizing power consumption during periods of stable weather conditions.

Source

A system that optimizes heating and cooling operation in commercial buildings by automatically adjusting temperature control based on weather forecasts. The system integrates with existing building management systems and weather forecasting data to determine optimal heating and cooling schedules. It monitors room temperature and weather conditions in real-time, adjusting heating and cooling operations to maintain consistent indoor temperatures while minimizing energy consumption. The system achieves this through a dynamic temperature control algorithm that adjusts heating and cooling thresholds based on current weather conditions and room temperature, rather than relying on traditional hysteresis controls.

Source

A method for optimizing HVAC system energy efficiency through predictive free cooling. The method enables precise weather-based control of chillers by integrating weather forecast data into the system's control logic. When ambient temperatures drop below a predetermined wet bulb threshold, the system automatically activates free cooling, optimizing energy savings by extending the free-cooling window period. This approach eliminates the need for manual monitoring and intervention, while providing real-time data-driven insights into free-cooling availability and usage patterns.

Source

Method for optimizing building temperature control through predictive energy management. The method integrates weather data and occupancy patterns to dynamically adjust building temperature setpoints. It calculates a compensation temperature based on both weather conditions and occupancy factors, then applies this temperature to the building's HVAC system. The compensation temperature is calculated using factors like window shading, solar radiation, and occupancy patterns, ensuring optimal energy efficiency while maintaining comfortable indoor temperatures. The method enables precise temperature control by continuously monitoring and adjusting the compensation temperature, rather than relying on traditional setpoint adjustments.

Source

Controlling heating and cooling systems in buildings based on user comfort levels calculated from factors like temperature, humidity, sunlight, and occupancy. The system uses sensors to measure these parameters in different areas of the building. It calculates a sensible temperature for each user based on factors like sunlight exposure and motion. It then adjusts the heating/cooling setpoints for each area to match the calculated sensible temperatures. This provides personalized comfort levels tailored to each user's experience rather than just the measured indoor temperature.

Source

Air-conditioning system with intelligent temperature control that automatically adjusts the temperature based on ambient conditions and user preferences. The system includes a control unit, a temperature sensor, and a user interface. The control unit continuously monitors environmental conditions and compares them to setpoint temperatures to automatically adjust the air conditioner's temperature. The system also enables remote temperature adjustments through a wireless connection to the control unit.

Source

Adjusting controller set points based on outdoor temperature to optimize indoor climate control. The system determines heating and cooling set point adjustments by comparing deviations from a predefined intermediate temperature range between heating and cooling set points. This approach enables dynamic temperature control across the temperature spectrum, allowing users to fine-tune their indoor comfort and energy efficiency while maintaining consistent indoor temperatures.

Source

Air treatment system that optimizes indoor air quality through personalized weather-based control. The system integrates weather data with real-time environmental conditions to deliver tailored air quality management. It uses a centralized database to match specific weather patterns with appropriate air treatment strategies, ensuring optimal indoor air quality while minimizing energy consumption.

Source

Automatically optimizing indoor air quality through real-time environmental monitoring and intelligent device control. The system integrates weather data, air quality sensors, and device configuration to dynamically adjust device operation based on environmental conditions. It ensures optimal device performance by automatically transitioning devices to optimal operating modes when air quality exceeds acceptable levels, preventing premature device activation. This approach enables continuous air quality monitoring and intelligent device control, ensuring both user health and environmental protection.

Source

A method for optimizing air conditioning system operation through real-time weather forecasting and predictive control. The method integrates weather data with control commands to dynamically adjust system parameters, ensuring optimal comfort levels. It employs a data processing platform that retrieves weather information, compares it to pre-set thresholds, and determines optimal control actions based on temperature trends. The platform then executes these control actions, continuously monitoring system performance and adjusting parameters as needed. This approach enables more precise temperature control by leveraging real-time weather data to anticipate and respond to changing conditions.

Source