Computerized systems and methods for providing protective safeguards within a location for items located therein
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Solution Overview
Problem
Current climate control systems lack the ability to dynamically adjust environmental conditions based on the specific characteristics of items and occupants within a location, potentially compromising their safety and integrity.
Innovation Solution
A decision intelligence-based framework using AI/ML techniques to determine and enforce safe environmental thresholds for temperature, humidity, and other conditions, integrating user input and sensor data to manage climate systems like HVAC, ensuring the safety of items and occupants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional climate control systems are used to maintain temperature according to zones, then basic temperature control is achieved, but the system cannot dynamically adjust environmental conditions based on specific characteristics of items and occupants, compromising their safety
Solution Approach 1:
The system dynamically adjusts climate control parameters based on real-time sensor data and AI/ML analysis. The thermostat continuously monitors environmental conditions and automatically modifies temperature, humidity, and air quality settings to protect sensitive items and occupants, transforming a static zone-based control system into an adaptive protective system.
Solution Approach 2:
The system changes multiple environmental parameters simultaneously (temperature, humidity, air quality) based on the specific characteristics of items and occupants detected in the space. AI/ML algorithms determine optimal parameter combinations to maintain safety thresholds for different scenarios, such as protecting artwork or ensuring pet comfort.
2Reliability
If AI/ML techniques are implemented to determine safe environmental thresholds, then dynamic protection of items and occupants is achieved, but system complexity increases
Solution Approach 1:
The thermostat device performs multiple functions: traditional temperature control, air quality monitoring, humidity management, and AI/ML-based safety threshold determination. By consolidating these diverse functions into a single multi-functional device, the system achieves comprehensive protection without proportionally increasing overall system complexity.
Solution Approach 2:
The system uses sensor data from the environment and items to automatically train and improve its own AI/ML models. The thermostat self-adjusts its protective parameters based on learned patterns, reducing the need for manual configuration and complex external control systems while maintaining high reliability.
Data Source
AI summary
Disclosed are systems and methods that provide a novel framework that automatically and dynamically adjusts and controls the real-world conditions of an environment within a location. Such adjustment can be based on characteristics of items and/or persons within a location, such that the integrity of the items are prevented from being compromised. The framework can function by determining and enforcing safe thresholds for environmental conditions (e.g., temperature and humidity, for example) using artificial intelligence and/or machine learning (AI/ML) techniques. Climate and environmental condition information within the location, as well as attributes/characteristics of the location and/or items therein can be accounted for, and leveraged in determining environmentally safe thresholds that can be utilized for monitoring the location. When real-world conditions in the environment approach and/or exceed the safe thresholds, a climate system (e.g., a HVAC, for example) can be triggered, which can effectuate remediation of the unsafe conditions.