In-situ monitoring is an important aspect of geotechnical projects to ensure safety and optimise design measures. However, existing conventional monitoring instruments are limited in their accuracy, durability, complex and high cost of installation and requirement for ongoing real time measurement. Advancements in sensing technology in recent years have created a unique prospect for geotechnical monitoring to overcome some of those limitations. For this reason, micro-electro-mechanical system (MEMS) technology has gained popularity for geotechnical monitoring. MEMS devices combine both mechanical and electrical components to convert environment system stimuli to electrical signals. MEMS-based sensors provide advantages to traditional sensors in that they are millimetre to micron sized and sufficiently inexpensive to be ubiquitously distributed within an environment or structure. This ensures that the monitoring of the in-situ system goes beyond discrete point data but provides an accurate assessment of the entire structures response. The capability to operate with wireless technology makes MEMS microsensors even more desirable in geotechnical monitoring where dynamic changes in heterogeneous materials at great depth and over large areas are expected. Many of these locations are remote or hazardous to access directly and are thus a target for MEMS development. This paper provides a review of current applications of existing MEMS technology to the field/s of geotechnical engineering and provides a path forward for the expansion of this research and commercialisation of products.

MEMS-based instruments have become more attractive in recent years for many industries, particularly geotechnical monitoring owing to their small size and low capital cost. However, overcoming nonlinearity errors is a major concern to ensure accuracy, precision, and repeatability of measurement. Nonlinearity error in measuring instruments can be solved using polynomial function of different degree based on severity of error. In this study, Lagrange polynomial fitting method is applied for nonlinearity calibration of a newly developed MEMS pore pressure sensor by means of optimum calibration points. A procedure for optimum selection of the calibration points to get the best calibration characteristics of a pore pressure sensor is investigated. For this work, the calibration characteristics are evaluated by Lagrange interpolation using special set of Chebyshev nodes, D, A and R-optimum points. The D-A-R optimum points are constructed by Imperialist Competitive Algorithm (ICA). The value of the optimal approach is also compared with a uniform approach using equidistant points through actual readings. The results show the increased accuracy and precision of measurement using optimum approach. This increased accuracy allows the application of MEMs to sense smaller changes in pore pressure readings providing unique opportunity for passive estimation of subsurface properties.

Groundwater level monitoring is critical to protect and manage of groundwater resources. A properly designed and executed instrumentation can play important role to increase the quality and reliability of collected data and reducing total monitoring costs. The efficiency of the instrumentation is mainly depending on the accuracy and reliability of the installed sensors. This study presents, the testing and application of a cost-effective pressure sensor (0-689 kPa) range) for water level monitoring based on microelectromechanical system (MEMS) technology and Internet of things (IOT) concept. The sensor performance in term of accuracy, precision, repeatability, temperature was investigated in laboratory columns (with constant water level, increasing and decreasing water levels at various rates) and in-situ conditions in an observation bore (with natural groundwater level fluctuations). The results shows that the MEMS sensor capable of providing reliable and adequate monitoring scheme with an accuracy of 0.31% full scale (FS) (2.13 kPa).