Many countries are increasing their research on monitoring technology to identify and systematically manage various domestic changes. In particular, the need for remote monitoring is increasing in response to climatic disasters, such as flooding, storms, and rising tides caused by global warming. We developed a smartphone-based environmental monitoring system that enables remote monitoring in any place and at any time. The overall system is composed of a 24-hour smartphone-based imaging system, a monitoring information management system to receive the monitoring information, and stereo image rectification software that provides lens distortion correction, geometric correction, and stereo matching of the monitoring images. The system was developed using the Samsung Galaxy S with the Android OS, as well as open source–based software and other hardware. It is easy to install, control remotely, and monitor the status of imaging devices. We assessed the accuracy of the micro-electro-mechanical system (MEMS) sensors of the smartphone to evaluate the applicability of our environmental monitoring system. The assessment was conducted via survey using metric cameras, a global positioning system receiver, a three-dimensional laser scanner and total station, geometric correction, and digital elevation models generated with camera internal elements, external elements, and ground control points. We demonstrated the effectiveness of the system, and showed that the accuracy of the MEMS sensor and camera calibration have a significant effect on image analysis.

This paper proposes a smartphone-based network real-time kinematic (RTK) positioning and gravity-surveying application (app) that allows semi-real-time measurements using the built-in Bluetooth features of the smartphone and a third-generation or long-term evolution wireless device. The app was implemented on a single smartphone by integrating a global navigation satellite system (GNSS) controller, a laptop, and a field-note writing tool. The observation devices (i.e., a GNSS receiver and relative gravimeter) functioned independently of this system. The app included a gravity module, which converted the measured relative gravity reading into an absolute gravity value according to tides; meter height; instrument drift correction; and network adjustments. The semi-real-time features of this app allowed data to be shared easily with other researchers. Moreover, the proposed smartphone-based gravity-survey app was easily adaptable to various locations and rough terrain due to its compact size.

Keywords: Distributed parallel computing, Geoid heights computation, MPI, OpenMP, Diskless-based PC Cluster Much research have been carried out using optimization algorithms for developing high-performance program, under the parallel computing environment with the evolution of the computer hardware technology such as dual-core processor and so on. Then, the studies by the parallel computing in geodesy and surveying fields are not so many. The present study aims to reduce running time for the geoid heights computation and carrying out least-squares collocation to improve its accuracy using distributed parallel technology. A distributed parallel program was developed in which a multi-core CPU-based PC cluster was adopted using MPI and OpenMP library. Geoid heights were calculated by the spherical harmonic analysis using the earth geopotential model of the National Geospatial-Intelligence Agency(2008). The geoid heights around the Korean Peninsula were calculated and tested in diskless-based PC cluster environment. As results, for the computing geoid heights by a earth geopotential model, the distributed parallel program was confirmed more effective to reduce the computational time compared to the sequential program.