Lest mountain slips

WHETHER it’s the mountains of Munnar in Idduki district of Kerala in the south or the Himalayan ranges in Uttarkashi region in the north, landslides are a common occurrence. They cause mass destruction year after year. The problem is that landslides are difficult to predict as they are very localised and depend on the soil conditions prevalent in a region. The methods in use to predict landslides depend on satellite data and geographical information system. But the results are often inaccurate as the methods study conditions superficially and fail to analyse what is happening at the micro-level.

To help predict landslides, scientists at Amrita Centre for Wireless Networks and Applications, a part of Amrita University in Kerala, have devised a system based on wireless sensor network. It is a first-of-its-kind system based on wireless technology in India and among the first in the world for predicting such mishaps. A wireless sensor network uses a variety of sensors to monitor physical conditions in an area. They can sense the changes in soil pressure, moisture, movement and transmit the information to a central processor. They are widely used for environmental monitoring, such as detecting levels of pollutants and forest fires.

How it works

The prediction system has been installed at Munnar’s Anthoniar Colony and consists of 150 geophysical sensors. These include moisture sensors which determine soil moisture by measuring dielectric constant (an electrical property dependent on moisture), strain gauges that measure strain in the soil, piezometers which measure the water pressure in soil pores, tiltmeters, that measure changes in soil-level, rain gauges and geophones, a device which converts landmass movement into voltage.

The sensors are connected to form 20 wireless sensor nodes. Each node is a combination of a sensor, a transmitter, an electronic circuit for interfacing with the sensors and an energy source, usually a battery. The real-time data generated by these sensors is sent to a field data management centre located a kilometre away and then transmitted to the University campus, situated about 252 kilometres away, for processing.

The university has developed a computer model to assess the data and issue warnings. For example, when the level of moisture increases over a certain level, the system raises an alarm.

The first-level warning is issued when the soil has more than 90 per cent moisture. Second-level warning is issued when the pore pressure value (pore pressure increases with rainfall) increases. This way, a warning can be sent out to the district authorities around 24 hours before a landslide occurs, giving enough time to evacuate people.

Costly affair

V S Prakash, director at Karnataka State Natural Disaster Monitoring Centre, points out that no compromises should be made when it comes to protecting human life. But the system is expensive, he says. It costs around Rs 5 crore. The researchers are trying to reduce the price by replacing costly sensors with cheaper alternatives. For example, the inclinometer used in the system costs around Rs 1 lakh. “It has now been replaced with tiltmeters which cost Rs 25,000 and provide equally good information,” says Maneesha Ramesh, director at the Centre who has set up the system at Munnar. She hopes the system can be replicated in other landslideprone areas. “The data produced by the sensors can be used in other fields like agriculture, where knowing the physical properties of the soil is crucial,” she adds.

M H Mehta, chairperson of the National Bioshield Society who is looking for ways to reduce the harm by landslides in Uttarkashi, says, “The experiment provides an opportunity to take steps to prevent landslides.” He suggests more trees should be planted to improve soil binding.

Other factors

Cost is only one of the concerns. Before such a system is used in the field, it is important to ensure that the data being transmitted by the sensors is secure, says Dawn Song, an expert in software security at University of California, Berkeley in the US. For this, one can incorporate protective software like BitBlaze that analyses malicious software code and WebBlaze that focuses on defending web-based applications and services against malicious software.

During a disaster, there is also the problem of overflow of data and lack of resources to handle it. Though ad hoc networks are generally put in place, these have limited bandwidth and crucial data can get lost. To avoid this problem Faisal Luqman and his team at Carnegie Mellon University in the US have developed a framework that is loaded on a smart device and prioritises data. For example, priority is given to information from a sender with low battery levels.

Apart from being used in disaster situations, such wireless technologies can also be put to use in an urban set up for managing traffic for instance, says P Venkat Rangan, chancellor of the university.

Wireless relief   While this might be the first time a wireless network has been employed for landslide prediction, wireless sensor technologies have been used for many other benefits. These applications use common wireless devices such as mobile phones and laptops. It is estimated that more than seven trillion wireless devices would be serving seven billion people by 2020. Some of the commonly used technologies across the world were discussed recently at a conference on wireless technologies for humanitarian relief. These include: TWIMIGHT Twimight is an open source Twitter application for android phones. This application helps victims communicate to each other through Bluetooth or WiFi Direct, which allows WiFi devises to connect to each other without a wireless access point. Twimight has a “disaster mode”, which the users can enable upon losing connectivity. Tweets are saved on the phone and passed when other victims are near. Information about all the connected victims can be gathered if even just one of the victims is rescued EMERGENCY CALLS A 911-like service has been developed in the US for WiFi-capable devices. This service enables victims to send emergency messages through any available access point irrespective of the fact that these might not be secured and protected. The emergency service in WiFi networks does not require authentication. The service is also capable of finding the approximate location of the user I-LOV In Germany, I-LOV uses a combination of wireless technologies for detecting and identifying location of trapped victims. The technologies can detect signals from both working and inactive cell phones of the victim. In case the victim does not have a phone, I-LOV uses ground-penetrating radar to detect victims. The information generated is then used by a system that processes the data and identifies location of trapped victims M URGENCY University of Maryland has launched an emergency smartphone application, M-Urgency. It allows instant sharing of video, audio and location information about any emergency with the University police. It is a context-aware application that gives a lot of information that’s not easy to convey through words. For example, if there are four M-Urgency calls about a fire in a building, the responders can see which portion is on fire. This can help the crew prepare before they reach the incident spot EPIMAP This yet-to-be developed system works in case of an epidemic outbreak. Its efficacy has been demonstrated in case of flu epidemic. It is a software which can be downloaded on smart devices. It can help identify people who have been in contact with a disease infected person by recording the proximity of the person’s smart device with other devices. Thus, it gathers information on human interactions within a community. The information is then used to develop mathematical models which show the spread of infectious diseases and the contacts can be vaccinated. This is crucial as funds and vaccine availability in developing countries are limited

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