Structural Health Monitoring involves installing multiple highly sensitive vibration sensors at various points of a structure, transmitting the data to a central server, and analyzing it using conventional modal analysis methods, signal processing, and artificial intelligence to assess the real-time condition of the structure and generate outputs that are easily understandable for all stakeholders. These outputs are continuously updated on mobile devices, allowing users to identify healthy sections, damaged areas, and parts requiring minor repairs. At the same time, the software provides detailed information about the structural stability and habitability.The images at the beginning of this page present a conceptual view of data processing for the Jahan Koodak building, while the image below this text shows a real implementation at the Rafsanjan Copper Mine. The green spectrum indicates the structure’s health, and in case of damage, the colors shift to yellow, orange, and red, representing increasing levels of severity.

Offshore oil platforms are exposed to erosion caused by corrosion, fatigue, and stresses related to harsh weather conditions and massive sea waves. These platforms are of two types: some extend down to the seabed, constructed directly on the ocean floor and rising tens of meters above sea level, while others are floating structures stabilized by anchoring to the seabed or mooring. All types of offshore platforms are vulnerable to environmental damage, making continuous structural health monitoring essential.Traditionally, inspection methods have relied on visual observation, which is not only labor-intensive but also lacks accuracy, and updating models based on field observations carries a high degree of uncertainty.In 2025, Geopersian Seismography Co. entered into a research contract with the Iranian Offshore Oil Company to undertake structural analysis of platforms, identify damage locations, and determine the extent of damage. This phase of the project demonstrates the capability of modal and vibration analysis methods in assessing the current condition of offshore platforms.The next phase involves equipping platforms with advanced vibration sensors, transferring data to a central server, and applying artificial intelligence and machine learning techniques, enabling the engineering department of the oil company to have real-time access to precise structural health information at all times.The images above show the contract signing with the Iranian Offshore Oil Company and the unveiling of a high-dynamic-range accelerometer developed by Geopersian Seismography Co. during the Oil Industry Exhibition in May 2025.