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Landslide Detection System: Design and Development Alexandre Melo Delfim, Elton Guilherme Rodrigues, Marcelo Bender Perotoni Federal University of ABC (UFABC)
ABSTRACT The design of a landslide detection remote sensing system is analyzed. The scope of the project focuses on areas with landslide risk, so that a safe and efficient early warning can be emitted for potential risk situations. The ground motion detection device has an Arduino microcontroller board and an Accelerometer as its main sensor. Information about earth movements that take place prior to the landslide are processed and then trigger warning signals. Earth movements prior to the actual sliding occur with small intensities, therefore the first challenge is a clear identification of these small amplitude movements and the ability to distinguish them from a false warning. A prototype was built altogether with a software procedure to classify the movements and trigger an effective warning. Keywords: Sensors Development, Soil, Wireless Sensor Network.
INTRODUCTION Landslides are common in Brazil specially during the rainy season, sometimes with casualties. Large areas of irregular habitation that spread on hillsides and riverbanks (slums or “favelas”) are constructed in a chaotic and unstructured way on steep slopes, therefore likely to be endangered with short and intense bursts of heavy rainfall. The soil with low capacity of absorbing the water becomes saturated, given the deforestation that took place on the slums terrain, originally covered with rich biodiversity areas such as the Atlantic Rainforest. In Angra dos Reis, Rio de Janeiro, an area known to be prone to landslides, a study was performed as to correlate the landslides with the pluviometry [1], which showed an exponential relation between the landslides and the rain intensity. The found relation helped forecast potential risk situations given that there is a reasonable rich information of the precipitation rate (mm of rain), locally available after several occurrences along the years. Coastal areas along the Parana state were also the target of a landslide detection system based on six vibrating wire Piezometers, one inclinometer and a tensiometer, alongside with a pluviometer [2]. They monitor not only the precipitation rate but also the earth humidity and soil movements. India has another risky areas where landslides can provoke disasters and casualties. A set of geophysical transducers were placed inside a tube placed in a borehole – a geophone, strain gauges, a moisture and a 35
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pore pressure sensor) [3]. To provide a fast warning in cases of danger, a wireless system was set up, connecting different tubes placed on a large area using WiFi (2.45 GHz, channel with 11 Mbps) and with the analysis remotely run on the gathered data – this remote link based on a satellite channel. A thorough study was performed to design and test sensors to evaluate landslides in Northeast Brazil [4]. The sensors used were strain gauges, moisture and sound sensors and accelerometers. A wireless sensor network (WSN) was used to transmit the data from these sensors. This work uses two basic sensors – accelerometer and moisture detector. The system has its information sent to an Arduino (open source microcontroller board) and uses a wireless channel to direct the information to a PC.
METHODOLOGY The applied methodology involved researching the literature, and from the presented design alternatives picking up the ones that were within the limited available budget and time for the project. The chosen components and systems had to be easily available, and the proof of concept of the design was performed using the limited and previously defined resources.
DEVELOPMENT The movement sensor must transform the material movement the water flow imposes on the soil into a readable electric signal, according to figure 1.
Figure 1. Principle of the landslide detection.
The block diagram of the designed system is presented in figure 2. A wireless channel is set to transmit the sensor data to a receiver, where an Arduino hooked up to a PC and a LCD display operate as Human Machine Interface. Two leds also signal the occurrence of a warning and the effective landslide. A logic inside Arduino detects and analyzes the sensor data to decide which condition should follow – normal, warning or landslide.
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Figure 2. Block diagram.
From the available used sensors, accelerometers were chosen due to their availability (due to their popularity inside the robotics community) and easy integration to Arduino. Accelerometers are transducers that transform the kinetic energy into an electric signal. Their technology can be capacitive, piezoelectric or piezoresistive; active (with conditioning circuit integrated to the sensor) or purely passive [5]. The chosen accelerometer, MPU 6050, contains 3-axis gyroscope and accelerometers, coupled to a 16-bits analog to digital converter whose output communicates with the external world through an I2C protocol. Since its main target is the use in mobile phones, it has a low cost and it is easily available. In addition to sensing the earth movement, a moisture detection can be coupled to the system, since it can show to which degree the soil has been impregnated with water. That way a combination of two independent variables ensures a higher degree of reliability to the system, therefore avoiding false warnings. Semiconductor moisture sensors are easily available, and with low cost. Their principle of operation can be based on the thermal conductivity, capacitive or resistivity [6]. Without the moisture signal, earth movements due to a nearby vehicle or other source could generate false alarms. The wireless channel is based on the chip nRF24L01, which operates in the unlicensed 2.4 GHz band (ISM – industrial, scientific and medical radio band). It can maintain up to 2 Mbps on the channel, with a transmitted power of 1 mW. The complete integrated system is shown in figure 3, alongside with the plastic container that accommodated it, to protect it from the earth and the humid environment. The I2C module performs the connection between the 16x2 LCD display and the Arduino, on the receiver side, and it is used to replace the direct connection using the Arduino digital I/O pins, which would otherwise require a large number of wires, increasing the likelihood of connection problems.
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Figure 3. Left, different modules and their connection and right the plastic container.
The software must decide whether which of the three conditions hold: •
Stable: neither rain nor soil movement detected;
•
Warning: high levels of moisture due to the water and small soil movements;
•
Landslide: high levels of moisture and large detected soil movements due to the acceleration measured with the accelerometer.
The logic uses the moisture level on the soil as a means to trigger the landslide Led alarm. The sensors are continuously read on a polling scheme, sequentially.
TESTS A testbed was constructed to test the system response, after its complete integration (figure 4). The plastic container was elevated and fixed in a definite angle, and later on toppled in two modes – fast and slow. Each test had the accelerometer three-axis readings recorded, as to check its sensitivity.
Figure 4. Testbed.
The results are shown in figure 5, for three different angles. The readings on the three axes are shown, their derivative is computed and detects the actual soil movement. Both fast and slow falls for the 30º and 15 º
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triggered the landslide alarm, whereas the 10 º determined the only warning led to be on. The system was seen to be sensitive enough to capture soil movements, and the wireless channel operate well within the distance of 5 meters.
Figure 5. Results from the accelerometer for different toppling angles.
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CONCLUSIONS The system was tested on a wet soil sample and the responses were calibrated to different angles. The wireless channel was proved operational, as well as the alarms and the LCD display. A movie was prepared containing the real test [7].
REFERENCES [1] SOARES, E. P. Caracterização da precipitação na região de Angra dos Reis e a sua relação com a ocorrência de deslizamento de encostas, 2006. Dissertação (Mestrado em Engenharia Civil) – Pós Graduação em Engenharia da Universidade Federal do Rio de Janeiro, 2006. [2] SESTREM, L. P. Concepção e implantação de um plano de instrumentação para avaliação das condionantes geotécnicas de uma encosta litorânea, 2012. Dissertação (Mestrado em Engenharia da Construção Civil) – Pós Graduação em Engenharia da Universidade Federal do Paraná, 2012. [3] RAMESH, M. V. Real-Time Wireless Sensor Network for Landslide Detection. 2009 Third International Conference on Sensor Technologies and Applications, pp. 405-409. [4] DE BRITO, G. G. Modelo de Monitoramento de deslizamento de encostas por meio de sensor multiparamétrico, 2013. Dissertação (Mestrado em Desenvolvimento de Processos Ambientais) – Pós Graduação em Desenvolvimento de Processos Ambientais da Universidade Católica de Pernambuco, 2013. [5] WEBSTER, J. G. The measurement, instrumentation and sensors Handbook. Boca Raton: Halit Eren, FL, 1999. [6] BALBINOT, A.V.J.B. Instrumentação e fundamentos de medidas. Rio de Janeiro: LTC. 2010. [7] TGIII_UFABC_Alexandre_Elton. Available at: https://www.youtube.com/watch?v=4VC4tX0CxLE
CONTACT INFORMATION Marcelo Bender Perotoni (corresponding author)
[email protected] Alexandre Melo Delfim
[email protected] Elton Guilherme Rodrigues
[email protected]
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