Remote Server-Based Heating Control with Autonomous Appliance Fallback
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Solution Overview
Problem
Conventional heating control systems in homes are inefficient, requiring manual adjustments and prone to incorrect temperature control, leading to energy wastage and potential safety issues, especially when the central control unit fails, resulting in temperature fluctuations that can cause freezing or overheating.
Innovation Solution
A remote server-based control system that calculates control limits for heating appliances using user-set target temperatures, house/room models, and outdoor environment data, enabling autonomous operation to prevent freezing and allowing remote user control, with cloud-based functionality and user-definable default settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual thermostat adjustment is used to maintain desired room temperature, then temperature control is achieved, but energy efficiency deteriorates and user convenience deteriorates
Solution Approach 1:
The system continuously monitors room temperature via temperature sensors and compares actual temperature against target temperature. Based on this feedback, the server automatically adjusts heating appliance operation to maintain desired temperature without manual intervention, eliminating energy waste from incorrect manual settings while ensuring reliable temperature control.
Solution Approach 2:
The control system performs self-adjustment by automatically calculating required heating power and controlling heating appliances based on real-time temperature data and pre-stored house models. This eliminates the need for manual thermostat adjustment while maintaining optimal temperature control and energy efficiency.
2Reliability
If manual thermostat adjustment is used to maintain desired room temperature, then temperature control is achieved, but user convenience deteriorates
Solution Approach 1:
The system automatically performs temperature control operations by monitoring temperature sensors, calculating required heating power based on pre-stored house/room models, and controlling heating appliances without user intervention. Users only need to set target temperatures once, and the system handles all subsequent adjustments autonomously.
Solution Approach 2:
The system continuously monitors temperature and automatically adjusts heating based on feedback from temperature sensors, eliminating the need for manual thermostat adjustments. This automated feedback loop maintains reliable temperature control while maximizing user convenience.
3Reliability
If heating appliance operates at high temperature setting, then desired room temperature is achieved, but energy consumption increases
Solution Approach 1:
Instead of setting heating appliances to high temperatures that exceed actual needs, the system calculates and applies only the partial heating power required to achieve target temperature based on real-time temperature feedback and pre-stored house models. This prevents energy waste from excessive heating while ensuring temperature reliability.
Solution Approach 2:
The system dynamically adjusts heating power parameters based on real-time temperature measurements and environmental conditions, rather than using fixed high temperature settings. This adaptive parameter adjustment eliminates energy waste from excessive heating while maintaining reliable temperature control.
4Ease of operation
If central control system is used for temperature control, then temperature management is achieved, but system reliability deteriorates when control unit fails
Solution Approach 1:
The system divides control functions between the server (central coordination) and local heating appliances with embedded controllers (independent execution). Each heating appliance can independently receive target temperatures from the server and autonomously control its own operation based on local temperature sensors, ensuring continued functionality even if central control fails.
Solution Approach 2:
House/room models and control algorithms are pre-stored in the system before operation. When control is needed, the system simply retrieves and executes these pre-prepared control instructions, enabling rapid autonomous response without requiring complex real-time calculations from the central server, thus maintaining reliability during server unavailability.
5Productivity
If heating appliance is positioned near windows, then heating efficiency is improved, but temperature distribution deteriorates
Solution Approach 1:
The system places temperature sensors at multiple locations including near windows and in the center of rooms to capture local temperature variations. The server receives these distributed temperature measurements and adjusts heating control to achieve uniform overall temperature distribution, allowing heating appliances to be positioned near windows for efficiency while maintaining stable temperature composition throughout the room.
Data Source
AI summary
A control system for controlling heating appliances in houses is provided. The control system includes a server arrangement that is spatially remote from the houses. The server arrangement is coupled via a communication network to at least one controller unit of the houses. Moreover, the heating appliances are provided with an autonomous control that is utilized in an event that the heating appliances fail to receive communications and/or instructions from their at least one controller unit during a set time period after last receiving communications and/or instructions.