Abstract: 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.