Landslide Early WarningSystem Application for Android
Landslide Early Warning System Application for Android
Early warning system maims to avoid and reduce the risk of damage and casualties caused by natural disasters. Landslides and earthquakes are natural disasters that often occur in Indonesia. The objective of the research is to develop landslide and earthquake early warning systemapplications for smartphone devices with Android operating system. Current smartphone containslow cost sensors able to detect movement. Despite of less accuracy than scientific instruments, but the ubiquity of smartphone can cover larger area. Crowdsourcing the data collection also reducesthe false positive rate caused by the sensor. We embed our prediction model in Android application to distinguishbetween earthquake and common human activity. Further, the data is sent to cloud server if predicted as earthquake. When the number of user reported the same event at the same time in certain area met the threshold, push notification then delivered to smartphone user which may have impact by the event. We use data from Sistem Informasi Kebencanaan–Longsorby Research Center for Geo technology to develop landslide early warning system. When smartphone user entering area with highly landslide potential, the would receive notification about the areapotential. This research uses Agile method to develop early warning system on Android device. Research activities are conducted in 6 (six) phases: requirement, plan, design, develop, release, track & monitor. In this paper,we described the process of design phase system that will be a guide in the next process in making the next
Dissemination of disaster information quickly and precisely requires a variety of efforts, including through the use of technology that has popularized. Indonesia territory is very wide with natural conditions often occur natural disasters. Sometimes the delivery of disaster events information to the community encounters obstacles. One of the factors is the information and early detection of disaster occurrence in a region or area is not known widely.The Indonesian smartphone user base experienced an average growth of 33% (Compound Annual Growth Rate from 2013 to 2017) based on Smartphone User Persona Report (SUPR) released by Vserv based on a study conducted by Nielsen Informate Mobile insights. Meanwhile, a survey conducted by APJII (Indonesia Internet Service Provider Association) in 2016 describedfrom the total population of Indonesia 256.2 million people, as many as 132.7 million have been using the internet and spread from the island of Sumatra to Papua. The survey results show 50.7% or approximately 67.2 million users use smartphones to access the internet with the type of content that is most widely accessed is social media 97.4% (129.2 million).Currently social media applications (such as twitter, facebook, whatsapp and others) have become part of the activities of Indonesian society. Various events often become trending topics in Indonesia even worldwide including various disaster events in Indonesia. By analyzing the data conveyed in the timeline, the landslide disaster information can be immediately communicated to the public.In addition, studies conducted by several universities and research institutes in Indonesia have placed sensors to detect potential landslides. The parameters measured as landslide potential arerainfall, land use, land slope, soil type and elevation. The occurrence of earthquakes is often addressed as well as a warning sign of the occurrence of landslides in a region.The Crowdsourced concept is one way to get certain services, ideas and content by asking for help from others in bulk, especially through online communities. This method began to be used for disaster mitigation applications, both for landslide information (potential events and landslide events) as well as earthquake detection. One of the earthquake detection research projects with crowdsourced was conducted by the University of Berkeley Seismology Laboratory through the MyShake project[3]. The MyShake application will record motion data through the accelerometer sensor on the smartphone and send it to the server for analysis. Data from the sensor will be validated to ensure earthquake or non-earthquake vibration data (false earthquake). In this app, smartphone devices only function as seismometers based on mobile devices.https://codeshoppy.in/
Communication between crowdsourced and cloud VPSusing data connection via GPRS (2G / 3G / 4G) and WiFi. Data exchange between crowdsourced and cloud VPSi.e.:•Crowdsourcedtransmits earthquake vibration data recorded by the accelerometer sensor and geolocation data. Earthquake vibration information is obtained through pattern recognition that corresponds to the machine learning pattern. •While the server will send notification of the occurrence of earthquake to all smartphone devices listed on the system. All devices are identified by the identity provided by the Android operating system. This identity will be sent as the device crowd sourced sends data. Additionally, the server sends the landslide information requested by the device based on the geolocation of the device. While the earthquake pattern update will be sent when there is a new pattern that is processed by service machine learning on the server.
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Early warning system maims to avoid and reduce the risk of damage and casualties caused by natural disasters. Landslides and earthquakes are natural disasters that often occur in Indonesia. The objective of the research is to develop landslide and earthquake early warning systemapplications for smartphone devices with Android operating system. Current smartphone containslow cost sensors able to detect movement. Despite of less accuracy than scientific instruments, but the ubiquity of smartphone can cover larger area. Crowdsourcing the data collection also reducesthe false positive rate caused by the sensor. We embed our prediction model in Android application to distinguishbetween earthquake and common human activity. Further, the data is sent to cloud server if predicted as earthquake. When the number of user reported the same event at the same time in certain area met the threshold, push notification then delivered to smartphone user which may have impact by the event. We use data from Sistem Informasi Kebencanaan–Longsorby Research Center for Geo technology to develop landslide early warning system. When smartphone user entering area with highly landslide potential, the would receive notification about the areapotential. This research uses Agile method to develop early warning system on Android device. Research activities are conducted in 6 (six) phases: requirement, plan, design, develop, release, track & monitor. In this paper,we described the process of design phase system that will be a guide in the next process in making the next
Dissemination of disaster information quickly and precisely requires a variety of efforts, including through the use of technology that has popularized. Indonesia territory is very wide with natural conditions often occur natural disasters. Sometimes the delivery of disaster events information to the community encounters obstacles. One of the factors is the information and early detection of disaster occurrence in a region or area is not known widely.The Indonesian smartphone user base experienced an average growth of 33% (Compound Annual Growth Rate from 2013 to 2017) based on Smartphone User Persona Report (SUPR) released by Vserv based on a study conducted by Nielsen Informate Mobile insights. Meanwhile, a survey conducted by APJII (Indonesia Internet Service Provider Association) in 2016 describedfrom the total population of Indonesia 256.2 million people, as many as 132.7 million have been using the internet and spread from the island of Sumatra to Papua. The survey results show 50.7% or approximately 67.2 million users use smartphones to access the internet with the type of content that is most widely accessed is social media 97.4% (129.2 million).Currently social media applications (such as twitter, facebook, whatsapp and others) have become part of the activities of Indonesian society. Various events often become trending topics in Indonesia even worldwide including various disaster events in Indonesia. By analyzing the data conveyed in the timeline, the landslide disaster information can be immediately communicated to the public.In addition, studies conducted by several universities and research institutes in Indonesia have placed sensors to detect potential landslides. The parameters measured as landslide potential arerainfall, land use, land slope, soil type and elevation. The occurrence of earthquakes is often addressed as well as a warning sign of the occurrence of landslides in a region.The Crowdsourced concept is one way to get certain services, ideas and content by asking for help from others in bulk, especially through online communities. This method began to be used for disaster mitigation applications, both for landslide information (potential events and landslide events) as well as earthquake detection. One of the earthquake detection research projects with crowdsourced was conducted by the University of Berkeley Seismology Laboratory through the MyShake project[3]. The MyShake application will record motion data through the accelerometer sensor on the smartphone and send it to the server for analysis. Data from the sensor will be validated to ensure earthquake or non-earthquake vibration data (false earthquake). In this app, smartphone devices only function as seismometers based on mobile devices.https://codeshoppy.in/
Communication between crowdsourced and cloud VPSusing data connection via GPRS (2G / 3G / 4G) and WiFi. Data exchange between crowdsourced and cloud VPSi.e.:•Crowdsourcedtransmits earthquake vibration data recorded by the accelerometer sensor and geolocation data. Earthquake vibration information is obtained through pattern recognition that corresponds to the machine learning pattern. •While the server will send notification of the occurrence of earthquake to all smartphone devices listed on the system. All devices are identified by the identity provided by the Android operating system. This identity will be sent as the device crowd sourced sends data. Additionally, the server sends the landslide information requested by the device based on the geolocation of the device. While the earthquake pattern update will be sent when there is a new pattern that is processed by service machine learning on the server.
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