The issue of sustainable development in building engineering has been discussed since the early 90’s. The current research seeks to aid in this endeavor by reducing the heating and cooling loads on a building through its envelope, more specifically the wall material. The problem as viewed by most researchers is that the most common building materials, such as concrete and steel, allow for easy heat and mass transfer into buildings. Researchers now look to earth-based materials as passive building materials for increased thermal regulation. The building envelope of earth-based materials is an important buffer for heat and mass transfer into the building environment, but is a part of a bigger picture, which includes hygrothermal loads from the occupants and other facets of the indoor environment, as well as the mechanisms that regulate the indoor environment. This research looks at the soil-based building materials in different light. Our premise is that an understanding of the analogies between thermoregulatory systems in skin, plant, and soils, would inspire us to use soils as intelligent materials in stabilized earth construction with their pore geometries engineered based on these analogies. This biomimetic approach of developing “geodermis” can be broken into two smaller problems: (1) “sensory/nervous systems” to collect and process surrounding hygrothermal data, and (2) “motor system” for semi-active hygrothermal control with the combination of passive regulation by soil and active regulation based on the information from the sensory/nervous system. The Auto Modulating Pattern Detection Algorithm (AMP) is a novel bio-inspired model-free data processing technique that extends the Hilbert-Huang Transform method to detect a “small” but important intermittent event of interest that is usually masked by “dominant” environmental disturbances in various monitoring applications. With AMP, higher detectability can be achieved by: (1) amplifying the amplitude of the pattern-changing event’s frequency characteristics in the time-frequency domain, (2) reducing the baseline frequency fluctuation in the time-frequency domain, and (3) increasing the temporal resolution of the energy-time-frequency domain signal.