Top PDF Measurement Design of Sensor Node for Landslide Disaster Early Warning System

Measurement Design of Sensor Node for Landslide Disaster Early Warning System

Measurement Design of Sensor Node for Landslide Disaster Early Warning System

The design of the tool starts with the creation of software on the Arduino IDE as a container for loading the programs needed in this tool. The initiation was carried out by entering the library of each component consisting of sensors 801S, DHT-22, 2 FC-28, MPU6050, and reed switches. For communication of module components initiated by Lora SX1278, and SIM900. Other components consist of RTC, relay and Fan. After initiation on void (Setup), the command is repeated repeatedly on Arduino in void (loop). Where at the time of loading this sensor reading is then changed in the form of the parameters of each sensor. After that it was done to find out the sensor values for landslide security parameters through ANN. Then the device will send an alarm to the receiver. At each reading the storage of the server and SD Card is carried out.
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Wireless sensor network design for landslide warning system in IoT architecture (review)

Wireless sensor network design for landslide warning system in IoT architecture (review)

II. T HE B ROADCAST -S TORM M ITIGATION S CHEMES One simple method to reduce the broadcast-storm is to use a probabilistic approach. The probabilistic based scheme uses probability mechanism for node selection rather than using a threshold mechanism (such as in distance-based threshold) for determining rebroadcast nodes. Basic broadcast techniques in VANETs follow either a 1-persistence or a p-persistence scheme. The 1-persistence scheme has the advantages of low complexity and high penetration rate, but creates massive redundancy. The p-persistence scheme may reduce message redundancy but may increase in total latency and degraded penetration rate. For example, literature [5] proposed three schemes: weighted p-persistence, slotted 1-persistence, and slotted p-persistence broadcast schemes, whilst literature [6] proposed an adaptive probabilistic based scheme that senses idle channel time to represent the broadcast probability.
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Earthquake Early Warning System Based On  Multiple Sensor Network

Earthquake Early Warning System Based On Multiple Sensor Network

Earthquake is one of the major natural calamity. So prediction of the reach of earthquake event to the various locations could result in minimizing the disaster due to it. This system contains the design of sensor system and the techniques used for detection and processing of the received signals in real time. In this system, an earthquake which is also known as a tremor or temblor is the result of a sudden release of energy in the Earth's crust that creates seismic waves. In this system, we use various sensors to detect the earthquake and alert us. Early warning systems can play an important role in reducing the negative impact of these catastrophic events on densely populated areas and in mitigating the damage to strategic structures and lifelines.
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Landslide Pre-Warning System Using Zigbee Based On Measurements of Wireless Sensor Network

Landslide Pre-Warning System Using Zigbee Based On Measurements of Wireless Sensor Network

ABSTRACT: At any time, any place the planet earth may get hit by any natural hazards, where huge losses occur including human as well as economic. These events cannot be stopped, but using some innovative techniques these losses may be avoided. Among these one of major natural hazard is landslide, which was recently occur in Pune (Malingaon (MH)).Taking these approach into consideration the design and improvement in the techniques must be developed for prevention of landslide hazard. There have been several techniques to determine the landslides risk and land movement. As it is quick and sudden movement, it is necessary to keep continuous eye on environment changes i.e. real time. To make it real time monitoring system for earth environment Wireless Sensor Network (WSN) use is best suited. These paper presents the pre-landslide alert system using WSN’s, where data transmission is done by GSM module and zigbee module. In the circuitry, microcontroller is used to read the measurement done by the Wireless sensors. If their occur any changes in set threshold values, then the alerts are made from GSM modem to transmit message wirelessly to server system, also voice output is transmitted from memory module used. Finally the security alarm is also generated using Zigbee.
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Design and challenges for a tsunami early warning system in the Marmara Sea

Design and challenges for a tsunami early warning system in the Marmara Sea

Since 1900, around 90,000 people have lost their lives in 76 earthquakes in Turkey, with a total affected population of around 7 million and direct losses of around 25 billion USD. Based on a time-dependent model that includes coseismic and post-seismic effects of the 1999 Kocaeli earthquake with moment magnitude Mw = 7.4, Parsons (J Geophys Res. 109, 2004) concluded that the probability of an earthquake with Mw > 7 in the Sea of Marmara near Istanbul is 35 to 70 % in the next 30 years. According to a 2011 study, an earthquake with Mw = 7.25 on the Main Marmara Fault is expected to heavily damage or destroy 2 to 4 % of around 1,000,000 buildings in Istanbul with a population around 13 million, with 9 to 15 % of the buildings receiving medium damage and 20 to 34 % of the buildings damaged lightly (Erdik, Science 341:72, 2013). In the absence of adequate post-earthquake assembly areas especially in the heavily urbanized Istanbul, it is evident that after a major earthquake, especially in the coastal parts of the city, citizens would be storming to landfill assembly and recreational areas. Besides earthquakes, around 30 tsunamis have been reported by Alt ı nok et al. (Natural Hazards Earth System Science 11:273 – 293, 2011) in the Marmara Sea. Among those, catastrophic earthquakes such as 1509, 1766, and 1894 resulted in considerable tsunamis and some damage. The latest tsunami observed in Marmara was due to a triggered submarine landslide of the 1999 Mw = 7.4 Kocaeli earthquake which led to reported run-up heights of 1 – 3 m in most places (Tinti et al., Marine Geology 225:311 – 330, 2006). In this study, I propose a design for a tsunami warning system specific for the Marmara region that is strongly coupled with the earthquake early warning system (due to the short arrival times of tsunami) and stakeholders of the tsunami mitigation activities, such as local and regional components of disaster and emergency management and civil protection units, to ensure that the citizens would remain away from the coastline in case of a large earthquake, while discussing associated challenges such as decoupled earthquake and tsunami mitigation activities in the Marmara region.
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Earthquake Early Warning System for Android

Earthquake Early Warning System for Android

---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Earthquake often inflicts severe casualties and property losses. Building information data play an important role in earthquake damage evaluation and emergency counter measures. Landslides and earthquakes are natural disasters that often occur in tamilnadu is a state of India. The objective of the research is to develop landslide and earthquake early warning system applications for smart phone devices with Android operating system .To enhance current earthquake warning systems, rising technologies, including social and mobile computing, have been the focus of much attention. As smart phones have benefitted from significant development over the last few years, it is now possible to capture various kinds of motion using a smart phone's sensors, (e.g., accelerometer, vibration, etc.) including earthquake motion. To that end, we developed smart phone software to capture and backend analytics to determine whether the motion captured by a smart phone is caused by an earthquake or by human motion. In so doing, our goal is to establish a new type of seismic network using smart phones which enhance traditional seismic networks. In this paper, we evaluated the use of smart phones as detection devices; collected both human and simulated earthquake data using the smart phones, and developed an algorithm to distinguish earthquakes from human activities. Our results show that using our algorithms, a smart phone or computer can not only be used as a recording instrument, but also a highly accurate earthquake detection tool. As a result, creating networks of axis sensors based on smart phones will enhance the safety of communities vulnerable to earthquakes, worldwide. The gateway which has the sensor node receiver and acts as an IOT transfers the warning to smart phones. Finally, many of the human lives can be saved.
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Design of Early Warning System Based on Wireless Sensor Network

Design of Early Warning System Based on Wireless Sensor Network

The Coimbatore University in India, in cooperation with the European Commis- sion and the Indian Space Research Organization, has developed a wireless sensor network monitoring system for landslide monitoring. The system is part of the WINSOC (wireless sensor network with self-organization capabilities for critical and emergency applications) research project [10]. Through the installation of sensor nodes to 15 meters below the surface, a variety of soil parameters were collected, such as soil moisture, vibration and displacement. Monitoring data is transmitted to Coimbatore University campus via a wireless base station. Through the background processing, warning and forecast of landslides are realized. The system places the sensor node 15 meters below the surface. It affects the reliability of wireless commu- nication between nodes. In addition, in order to implement data communication be- tween underground nodes and surface nodes, the node's RF transmission power is set to be larger, which reduces the life cycle of nodes and affects the overall system per- formance.
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Early Warning System of Landslide Disaster using Generalized Neural Network Algorithm (review)

Early Warning System of Landslide Disaster using Generalized Neural Network Algorithm (review)

Literature [1, 2, 3, 4] provides legacy single-attribute broadcast schemes (e.g. distance-based, location-based, and counter-based) that demonstrate the sender-to-receiver distance or number of message copies can be used to select the broadcast candidates. The use of speed differential between the sender and the receiver is also proposed. In [5], the speed is considered as a representation of vehicle density. Lower speed implies higher vehicle density. Literature [6] combined the use of the counter-based and the probabilistic schemes. The number of message copies heard during the waiting period is used to determine the vehicle's broadcast probability. In [7], local node density is used in DECA protocol to select broadcast candidates. Vehicles will be selected to broadcast a message if they have the highest number of neighbors. Upon a message has been received, every node checks if it is the selected rebroadcast node. If so, it broadcasts the message, otherwise it stores the message for future needs.
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An integrated methodology to develop a standard for landslide early warning systems

An integrated methodology to develop a standard for landslide early warning systems

In telemetry-based monitoring, every movement at the ground and slip surface, rainfall intensity–duration, and groundwater fluctuation are recorded by sensors and trans- mitted to an operations control center. The local server an- alyzes the data by taking into account the critical limit of ground movement and rainfall intensity–duration. Cautious- ness is important in installing the early detection sensor in high-risk zones with a high number of people at risk. De- termination of the installation location is based on zonation of landslide risk. The installation should be done together with the locals so that they develop a greater sense of be- longing and responsibility towards the devices and an entire system. The devices should be installed appropriately taking into account the geological condition, the existing symptoms, and landslide volume and potentially affected area. To real- ize a community-based landslide early warning system, the monitoring and early detection devices should use the most effective and adaptive technology (Fathani and Karnawati, 2013). Once the devices are installed, the teams are formed, the evacuation map and SOPs are made available, and an evacuation drill is conducted to ensure the functionality of the devices and the community’s responses. This annual drill will embody the “risk consciousness” as mentioned in the study by Jaiswal and van Westen (2013). Evacuation drills are carried out based on a scenario drawn up according to the SOPs (Table 1). They serve to train vigilance, preparedness, and responsibility of the disaster preparedness team during the time that the early detection devices indicate potential landslide. In addition, the evacuation drill also aims to intro- duce and familiarize the local community with the sounds of the sirens from each stage of the early detection devices, and to train people for evacuation.
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Early Warning System: An Assessment of Vulnerability

Early Warning System: An Assessment of Vulnerability

enter a marked slowdown in growth after a prolonged boom in economic activity fueled by rapid credit creation. 4 This dramatic surge in credit is, in large part, explained by heavy capital inflows and partly by the reform of the financial system, which is accompanied by drastic reductions in reserve requirements. Overall, the explosive growth in these countries comes to an end with a real appreciation of the domestic currencies (which are, in differing degrees, tied to the U.S. dollar) and the corresponding loss of export markets. It is noteworthy that during the latter part of this period there is a substantive appreciation of the dollar vis-a-vis the yen.
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Earthquake Early Warning System (EEWS)

Earthquake Early Warning System (EEWS)

catastrophic and cause huge loss of life and widespread destruction of infrastructure in the region surrounding the epicentre. In the recent years, we have seen large causalities and destruction in Gujarat and Nepal. To reduce these losses earthquake early warning system is must. With the advancement of technology particularly in the field of seismic sensors, embedded technology, wireless networks, IoT and cloud computing, it is possible to develop low cost advance earthquake monitoring and warning system using Wireless Sensor Network (WSN).The ability to anticipate and predict the earthquake through scientific means will give the time needed to escape and survive. Two types of waves are generated whenever earthquake occurs namely, P-waves and S-waves. EEWS is based on IoT supported protocols for disaster management. In this paper these protocols are discussed. There are several IoT-based cost effective solutions available in market for earthquake detection, which are also discussed in this paper.
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The Early Warning System:
an evaluation study

The Early Warning System: an evaluation study

explained on the basis of intergovernmentalism theory. Before the 1990's there was a lack of input legitimacy within the European Union. This became clear after the Danish citizens voted in a referendum against the Treaty of Maastricht in 1992 and the French citizens almost rejected this treaty. Parliaments came to be seen as important actors for reducing the democratic deficit within the EU (Norton, 1998). Because of this, parliaments got more formal instruments with which they can exert influence at EU-level (van den Berg, 2011). An example of a formal instrument is the Early Warning System, where parliaments have the opportunity to issue a yellow or orange card when they have the opinion that a legislative proposal of the Commission breaches with the subsidiarity principle (European Commission, 2009).
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Pre Earthquake Early Warning System

Pre Earthquake Early Warning System

The Devastation assist system will be helpful in any sort of catastrophe. Its main purpose is fast and accurate flow of information, help and rescue operation under adverse situation. As we know that the death rate and the number of casualties increases if right information is not able to reach in right (short) time. So, we thought of creating System of Web and App which will help achieve this.

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Multi-sensor data fusion for geohazards early warning system – an adapted process model

Multi-sensor data fusion for geohazards early warning system – an adapted process model

make up for errors in upstream processing. Data fusion processing cannot correct errors (or failures) in processing of individual sensor data. (3) Sensor fusion can cause poor performance or even a corruption of the fused results if incorrect information about sensor performance is used. (4) There is no magic or golden data fusion algorithm which is optimal under all conditions. Frequently, many practical applications rarely meet the underlying assumptions required by data fusion algorithms. (5) There will never be enough training data in practice. (6) It is difficult to quantify the value of a data fusion system. While measures of performance (e.g. probability of correct identification or observation accuracy) can be obtained, measures of mission effectiveness (e.g. probability of survival) are difficult to define. (7) Fusion is not a static process, but rather an iterative dynamic process that attempts to continually refine the estimation about the situation and threat environment. To avoid the pitfalls described above, some recommendations for system implementers and designers are given by D. L. Hall and Garga (1999). Suggestions include: (1) Perform a systematic analysis of sensor observing ability and then link the observable phenomena to required inferences. (2) Select commensurate algorithms for sensor pre-processing to mostly extract the information from the sensor data. (3) Perform a systematic algorithm selection based on the realistic availability of requisite prior data and make tradeoffs with the evaluation of real sensor data. (4) Use hybrid approaches such as hybrid pattern recognition techniques to overcome the limitations caused by a lack of training data. (5) Quantify the utility of a data fusion system for the purpose of supporting a human user to make more effective decisions. (6) Refine and adapt the dynamic data fusion process to assure the validity of fusion products.
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Design of Measurement Memory System Based on MEMS Acceleration Sensor

Design of Measurement Memory System Based on MEMS Acceleration Sensor

Abstract—With the rapid development of MEMS technology, MEMS ac- celeration sensors have been used more and more widely due to their unique advantages. Taking MEMS acceleration sensor as the core device, a measure- ment memory system was designed. The system mainly included acceleration detection module, acceleration memory module and control display module, which could realize real-time acceleration measurement and memory, and up- loaded the stored data to the computer. The vibration test was used to detect the performance of the system. Result showed that the system could achieve the de- sired effect, and realize real-time acceleration measurement and memory within the allowable error range. The system possessed strong resistance to high overload capacity, which could still work normally under the condition of the maximum overload of at least 100g.
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Influence of uncertain identification of triggering rainfall on the assessment of landslide early warning thresholds

Influence of uncertain identification of triggering rainfall on the assessment of landslide early warning thresholds

Quantitative assessments of the influence of the sources of errors listed above are difficult to be based on observational datasets, since it cannot be ensured that these are immune of errors. In this paper we capitalize on the synthetic rainfall– landslide dataset of a preceding study (Peres and Cancelliere, 2014), to quantify the effects of the imprecise identification of triggering rainfall on the assessment and performances of landslide-triggering thresholds. The dataset is in princi- ple “error-free” in the sense that the instants of landslide- triggering are exactly known, as well as the triggering rain- fall time history. We then fictitiously introduce errors in the triggering instants and in the rainfall series based on hypo- thetical scenarios of landslide data retrieval and analysis, and analyse the implications on the accuracy of ID thresholds. The quality of information available in real datasets is gen- erally intermediate of that corresponding to the hypothesized scenarios. These scenarios are combined with different crite- ria for event rainfall identification, and different aggregations of rainfall data (hourly and daily, and daily in the presence of a shift due to manual collection of data), so the effects of these other two sources of uncertainty are analysed as well (items i and ii of the above list). The synthetic data used for our analyses are based on characteristic for hillslopes in the landslide-prone region of Peloritani Mountains, in northeast- ern Sicily, southern Italy.
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Design and Development of Low Power Sensor Node For Plant Monitoring System    

Design and Development of Low Power Sensor Node For Plant Monitoring System    

A special interest and attention is given in choosing the microcontroller .Here controller belongs to Kinetis KL25 Sub-Family (KL25Z128VFM4). It is a Cortex-M0+ based microcontroller which is of 48MHz. It has a USB. By keeping efficiency in mind it has been designed.Compatible with all other Kinetis L families as well as Kinetis K2x family .It has General purpose MCU with USB 2.0, featuring market leading ultra low-power to provide developers an appropriate entry- level 32-bit solution. Here in this project the main purpose of using KL25Z128VFM4 is for 16 bit analog to digital conversion and for low power mode in order to design the lower power sensor node.
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Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application

Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application

al., 2013), as well as for early warning and forecasting (Intri- eri et al., 2012; Carlà et al., 2016a, b; Lombardi et al., 2016). GB-InSAR systems probably reveal their full potential in emergency conditions. They are transportable and only re- quire from a few tens of minutes to a few hours to be installed (depending on the logistics of the site). Moreover, they can detect “near-real-time” area displacements, without access- ing the unstable area, 24 h a day and in all weather conditions (Del Ventisette et al., 2011; Luzi, 2010; Monserrat et al., 2014). On the other hand, some limitations reduce the GB- InSAR technique applicability: first of all, the scenario must present specific characteristics in order to reflect microwave radiations, maintaining high coherence values (Luzi, 2010; Monserrat et al., 2014); only a component of the real dis- placement vector can be identified (i.e., the component par- allel to the sensor’s line of sight); and maximum detectable velocities are connected to the time that the system needs to obtain two subsequent acquisitions. Sensors need power supply that, for long-term monitoring, cannot be replaced by batteries, generators or solar panels.
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A Study on Landslide Disaster Management

A Study on Landslide Disaster Management

ABSTRACT :Landslide Disaster Management study need for the particular area where it is frequently occur and also where its occurrence badly affected to the routine activity. Any route either it is of railway or roadway or any other structure require to geological study and engineering study. As the soil is natural material and containing very complex structure it is very important to make proper study and evaluation so that it does not fail in shear as it leads to landslide. here in this paper from studying along some route in Maharashtra region, India. In this study route contents very important projects such as National Highway and the railway route.
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ENERGY EFFICIENT SENSOR NODE DESIGN IN WIRELESS SENSOR NETWORKS

ENERGY EFFICIENT SENSOR NODE DESIGN IN WIRELESS SENSOR NETWORKS

The number of wireless sensors is typically considered as wireless sensor networks. The real time applications of wireless sensor network have been increased recently and this will increase even more in the next years. However for the full deployment of wireless sensor network introduces energy consumption problem. Previous research includes duty cycling and data driven approaches. Duty cycle-fraction of the time node will be in active mode. Duty cycling can be achieved using sleep/wake up protocol and mac protocol. Sleep/wake up protocol uses sparse topology and energy management approach to improve the network life time by setting some of the redundant nodes to be in sleep mode. The traffic adaptive medium access protocol is designed to reduce the energy consumption by assigning the nodes to low power idle state whenever they are not in transmission or reception mode. Disadvantages of duty cycling approach: not aware of which data is sampled by the sensor nodes. So the data driven approach is used. In data driven approach there are two categories: data compression and energy efficient data acquisition. For data compression the wavelet transforms and for energy efficient data acquisition, duty cycling and adaptive sampling is used. Other approaches for energy aware transmission includes modulation scaling scheme, multi hop routing scheme, network sectioning and low power hardware. Motivated by prior research the node-level energy saving is achieved by adaptive radio frequency power setting and the network level energy saving is achieved by adaptive network configuration. This paper is the extension of the above which includes periodic sleep/wake up scheme to further achieve node-level energy saving.
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