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The rise against landslides: Big Data to the rescue

  • New system a huge improvement over traditional, labour-intensive methods
  • Mapping, 3-D scanning, smart sensing — all combine to create cohesive ecosystem

CURRENT slope monitoring exercises are carried out manually. Several methods are being used to monitor slope movements. Some of the most common are satellite imageries and conventional Global The rise against landslides: Big Data to the rescuePositioning System (GPS) which require manual observations.
Others prefer to use 3D laser scanners that can scan any topography and provide quick assessments of the slope. Though these methods are efficient in monitoring slope movements, they lack real-time monitoring and predictive analytics of when landslides will happen.
To help tackle the issue of slope management and monitoring, Pembinaan TMC Sistem Sdn Bhd has taken the leap into Big Data and Analytics and has come up with a revolutionary solution. They developed a remote landslide sensing system with Predictive Monitoring and Early Warning Solution known as Integrated Deformation Early-warning Alert Solution (IDeas). This new system is a huge improvement over the traditional, labour-intensive and costly methods of slope monitoring.
IDeas uses mapping, 3-D scanning and smart sensing—all combined together to create one cohesive ecosystem that is able to analyse and predict slope movements, thus preventing landslides. This state-of-the-art integrated solution runs on a cloud platform, allowing the company to easily scale their resources, making the system flexible and cost-effective.
The concept being used is to measure the displacement of prisms fixed on selected critical points on the slope or monitored structure. Then, the position (x.y,z) will be surveyed to produce a set of reference points for displacement calculation. Theoretically, if there is no movement, the position of the prisms will never change. If there are any differences in the measured positions, it can be interpreted that there is soil movement or worse, a landslide. The measurements will not only indicate the size of displacement, but the direction of soil movement as well.
If the displacement value is bigger than the acceptable defined tolerance, it will trigger an alarm and send out warnings to respective personnel via SMS, email and social media. Realtime monitoring might warn you when a movement is detected; sometimes, however, by the time movements are detected, it could be too late. 
IDeas has been used in a Malaysian gold mine, one of TMC’s target industries. As safety is paramount in the mining industry, serious damages of life lost due to landslides will lead to the mine being shut down for investigations. With IDeas, the gold mine in Malaysia minimized their risk of a landslide which could potentially cost them US$1.5 million for every week its operations are disrupted.

[Beginning October, in a commercial arrangement, DNA will feature every article in a special 2015 pdf book, the Malaysian Digital Economy Corporation (MDEC) produced called, Exposing the Promise of Big Data Analytics: Case Studies in Malaysia. Where relevant, a link is provided at the end of each case study to download the full version.]

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