scholarly journals Sistem Monitoring Tanah Longsor Berbasis Internet of Things dan Geographic Information System

2019 ◽  
Vol 3 (02) ◽  
pp. 70-77
Author(s):  
Roni Wahyu Putra ◽  
Haris Suryamen
Keyword(s):  
Information System ◽  
Soil Moisture ◽  
Geographic Information System ◽  
Internet Of Things ◽  
Natural Disasters ◽  
Success Rate ◽  
Rainy Season ◽  
Sensor Data ◽  
Material Loss ◽  
Loss Of Life

Landslide is one of the natural disasters that happens quite often in many parts of Indonesia. Landslide brings negative aspects to people because it causes material loss and loss of life. Landslides generally occur in the rainy season with high rainfall. In this research, a system is made to predict the chance of landslide to happen by measuring the level of rainfall, soil moisture, and soil displacement, and send the sensor data and position of a landslide to the database. According to this research, the system can predict the chance for the landslide to happen and give a warning with a 100% success rate.

scholarly journals Decision Making in the Context of Natural Disasters Based on a Geographic Information System and the Internet of Things (IoT)

2021 ◽  
Author(s):  
Aissa Bensattalah ◽  
Rachid Chalal ◽  
Tahar Hassaine Daouadji ◽  
Tayeb Bensattalah
Keyword(s):  
Decision Making ◽  
Information System ◽  
Geographic Information System ◽  
Internet Of Things ◽  
Natural Disasters ◽  
Geographic Information ◽  
Decision Makers ◽  
The Internet ◽  
Structure Interaction ◽  
The Internet Of Things

Decisions within the company, managers in countries or regions are made by one or more groups of decision-makers. The management of natural disasters involves several specialized decision-makers (experts, firefighters, police officers, drivers,). The aim of the chapter is to improve decision making in the context of natural disasters situation. Zero risk in the world does not exist due to natural phenomena that occur randomly and appear suddenly. It is essential to manage the risks in the situation of natural disasters and also to confront the influence of natural disasters on the phenomenon of Soil-Structure Interaction. For this, this chapter presents a conceptual architecture of a knowledge base to manage the risks of natural disasters remotely by a Geographic Information system (GIS) and embedded systems. This architecture is based on the integration of data via different sources of information (GIS, satellites, electronic sensors and comments from experts). To properly manage this information, this chapter uses the ontology of Soil-Structure Interaction With Agents External (OSSIWAE) in the context of the Internet of Things (IoT). A case study is conducted on a prototype of a model for building a structure three-story for testing the usability of the proposed architecture.

ANALISIS KONDISI BAWAH PERMUKAAN DAN RISIKO BENCANA TANAH LONGSOR UNTUK ARAHAN PENATAAN KAWASAN DI DESA TENGKLIK KECAMATAN TAWANGMANGU KABUPATEN KARANGANYAR JAWA TENGAH

2013 ◽  
Vol 13 (2) ◽  
Author(s):  
Heru Sri Naryanto
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Regional Planning ◽  
Rainy Season ◽  
Great Influence ◽  
Landslide Risk ◽  
Potential Hazard ◽  
Volcanic Deposits ◽  
Steep Topography ◽  
Steep Slopes

Karanganyar District is a hilly area with steep slopes, rock constituent of young volcanic deposits of Lawu Volcano products, thick soil and relatively high rainfall, so it is potential for large landslides in this region. The landuse in the Karanganyar District including the Tengklik Village is generally dominated by rice fields, seasonal gardens and settlements. Plantation made up in areas with steep topography has great influence on erosion and landslides. Similarly, many settlements are built on a slope so that the area is very vulnerable to the threat of landslides. In the rainy season landslides are common. The potential hazard of landslidesoccurred in 14 sub districts in Karanganyar District. Large landslides have occurred in Karanganyar on December 26, 2007 which claimed the lives of 62 people, with the greatest victims were in the Ledoksari Village, Tawangmangu. The Tengklik Village has already experienced creep type landslides, which have destroyed settlements, roads, seasonalgardens and all existing infrastructure in the area. In order to do the proper handling and anticipation of a catastrophic landslide, a variety of technological applications landslides using geographic information system (GIS) was then carried out, to detect the configuration of 2D geoelectrical subsurface prone areas for landslide risk study and regional planning.

scholarly journals ANALISIS POLA HUJAN DAN DISTRIBUSI HUJAN BERDASARKAN KETINGGIAN TEMPAT DI PULAU FLORES

2020 ◽  
Vol 5 (2) ◽  
pp. 118-128
Author(s):  
Elisabet Marlin Lesik ◽  
Hery Leo Sianturi ◽  
Apolinaris S Geru ◽  
Bernandus Bernandus
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Rainy Season ◽  
Geographic Information ◽  
Rainfall Data ◽  
Mean Values ◽  
Randomized Design ◽  
Average Rainfall ◽  
Completely Randomized Design ◽  
Rainfall Patterns

Abstrak Telah dilakukan analisis pola dan distribusi hujan berdasarkan ketinggian tempat di pulau Flores. Data rata-rata bulanan untuk mendapatkan pola curah hujan, data curah hujan harian ke dasarian untuk mendapatkan data curah hujan dan data periode curah hujan selama musim hujan. Penelitian ini menggunakan software Geographic Information System (GIS) untuk membuat peta distribusi curah hujan dan di analisis menggunakan metode Rancangan Acak Lengkap (RAL) untuk mendeteksi perbedaan nilai tengah variabel pengamatan pada elevasi yang berbeda. Berdasarkan grafik pola hujan yang ada di pulau Flores adalah pola hujan monsunal. Hasil dari perhitungan menggunakan RAL, diperoleh nilai populasi pengamatan P1 pada ketinggian tempat (0-300 m dpl) dengan curah hujan rata-rata 851,75 mm dan periode musim hujan rata-rata 10,50 dasarian. P2 pada ketinggian tempat (301-600 m dpl) memiliki curah hujan rata-rata 1367,75 mm dan periode musimhujan rata-rata 13,75 dasarian. P3 pada ketinggian tempat (601-900 m dpl) memiliki curah hujan rata-rata 1875,25 mm dan periode musim hujan rata-rata 15,75 dasarian. P4 pada ketinggian tempat (901-1200 m dpl) memiliki curah hujan rata-rata 3164,50 mm dan periode musim hujan rata-rata 22,25 dasarian. Hal ini menunjukan ketinggian tempat memiliki pengaruh terhadap curah hujan dan periode musim hujan di pulau Flores.Kata Kunci: Pola hujan; curah hujan; periode musim hujan; Geographic Information System (GIS); Rancangan Acak Lengkap (RAL). Abstract An analysis of rainfall patterns and distribution based on altitude on the island of Flores has been done. Monthly average data to get rainfall patterns, daily to basic rainfall data to get rainfall data, and rainfall period data during the rainy season. This study used Geographic Information System (GIS) software to create rainfall distribution maps and is analyzed using the Completely Randomized Design (CRD) method to detect differences in mean values of observational variables at different elevations. Based on a chart of rain patterns on Flores island is a monsoonal rain pattern. The results of calculations using RAL, observational population obtained values P1 at altitude (0-300 m asl) with an average rainfall of 851.75 mm and an average rainy season period of 10.50 dasarian. P2 at altitude (301-600 m asl) has an average rainfall of 1367.75 mm and an average rainy season period of 13.75 dasarian. P3 at altitude (601-900 m above sea level) has an average rainfall of 1875.25 mm and an average rainy season period of 15.75 dasarian. P4 at altitude (901-1200 m asl) has an average rainfall of 3164.50 mm and an average rainy season period of 22.25 dasarian. This shows that altitude has an influence on rainfall and the rainy season period on Flores Island. Keywords: Rain patterns; rainfall, periods of the rainy season; Geographic Information System (GIS); Completely Randomized Design (CRD).

scholarly journals INTEGRAÇÃO IOT E GIS: UMA REVISÃO SISTEMÁTICA DE SUAS APLICAÇÕES

2020 ◽  
Vol 21 (78) ◽  
pp. 93-116
Author(s):  
Iran Carlos Caria Sacramento ◽  
Vivian de Oliveira Fernandes ◽  
Emerson De Andrade Marques Ferreira
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Internet Of Things ◽  
Geographic Information

A Internet of Things (IoT) está levando inúmeros benefícios para a vida humana por meio de serviços inteligentes. Com o crescimento massivo dos grandes conjuntos de dados dinâmicos, a aplicação de novos métodos para integração de tecnologias vem se tornando mais diversificados do que antes. Assim, o Geographic Information System (GIS) aparece como uma plataforma acessível, visto que, os métodos de gerenciamento e/ou monitoramento requerem uma múltipla fusão de informações. Este artigo visa analisar através da estatística descritiva as diferentes abordagens, contribuições e soluções quanto as aplicações relacionadas à integração da IoT e o GIS. A Revisão Sistemática de Literatura (RSL) foi utilizada enquanto método de pesquisa, envolvendo as seguintes etapas: (a) planejamento da revisão, (b) técnica de seleção e (c) análise dos resultados.  Os resultados possibilitaram evidenciar lacunas de pesquisa, vantagens e desvantagens quanto aos métodos investigados. As áreas de aplicação identificadas envolvem a segurança, operação e manutenção, saúde, tráfego e mobilidade urbana, arquitetura para implementação de sistema, agricultura de precisão e monitoramento ambiental. Considera-se que as abordagens relativas a IoT e ao GIS dispõe de uma grande diversidade de ferramentas para a exploração destas tecnologias, demonstrando que esta integração está em pleno desenvolvimento.

scholarly journals Photo-based automatic 3D reconstruction of train accident scenes

2016 ◽  
Vol 232 (1) ◽  
pp. 144-158
Author(s):  
Zhao Tang ◽  
Yinyu Nie ◽  
Jian Chang ◽  
Jianjun Zhang ◽  
Fengjia Liu
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
3D Reconstruction ◽  
Emergency Management ◽  
High Accuracy ◽  
Reconstruction Method ◽  
Insufficient Information ◽  
Loss Of Life ◽  
Train Derailment ◽  
Accident Scene

Railway accidents place significant demands on the resources of, and support from, railway emergency management departments. Once an accident occurs, an efficient incident rescue plan needs to be delivered as early as possible to minimise the loss of life and property. However, in the railway sector, most relevant departments currently face a challenge in drawing up a rescue scheme effectively and accurately with the insufficient information collected from the scene of a train accident. To assist with the rescue planning, we propose a framework which can rapidly and automatically construct a 3D virtual scene of a train accident by utilising photos of the accident spot. The framework uses a hybrid 3D reconstruction method to extract the position and pose information of the carriages involved in an accident. It adopts a geographic information system and a 3D visualisation engine to model and display the landscapes and buildings at the site of a train accident. In order to assess and validate our prototype, we quantitatively evaluate our main algorithm and demonstrate the usage of our technology with two case studies including a simulated scene with an in-lab setting and a real train derailment scene from on-site pictures. The results of both are accountable with high accuracy and represent the ability of timely modelling and visualisation of a train accident scene.

Information Processing for Generating Recommendations Ahead of Time in an IoT-Based Environment

2017 ◽  
Vol 5 (4) ◽  
pp. 38-62
Author(s):  
Alexandros Bousdekis ◽  
Nikos Papageorgiou ◽  
Babis Magoutas ◽  
Dimitris Apostolou ◽  
Gregoris Mentzas
Keyword(s):  
Information System ◽  
Information Processing ◽  
Internet Of Things ◽  
System Design ◽  
Sensor Data ◽  
Real Time Processing ◽  
Time Processing ◽  
Potential Problems ◽  
Current Article ◽  
Design Requirements

The evolution of Internet of Things (IoT) has significantly contributed to the development of the sensing enterprise concept and to the use of appropriate information systems for real-time processing of sensor data that are able to provide meaningful insights about potential problems in a proactive way. In the current article, the authors outline a conceptual architecture and describe the system design requirements for deciding and acting ahead of time with the aim to address the Decide and the Act phases of the “Detect-Predict-Decide-Act” proactive principle, which are still underexplored areas. The associated developed information system is capable of being integrated with systems addressing the Detect and the Predict phases in an Event Driven Architecture (EDA).

Design and Development of a Smart Waterway System

2014 ◽  
Vol 1030-1032 ◽  
pp. 1988-1991
Author(s):  
Lei Peng
Keyword(s):  
Information Technology ◽  
Information System ◽  
Geographic Information System ◽  
Internet Of Things ◽  
Geographic Information ◽  
Transportation Infrastructure ◽  
Typical Structure ◽  
Key Technology ◽  
Modern Information Technology ◽  
Modern Information

Port and waterway is important transportation infrastructure, smart waterway system can improve the waterway’s management with modern information technology, such as database, network, internet of things, geographic information system, etc. This paper analyzes the typical structure of a smart waterway, introduce involved key technology in the construction of smart waterway.

scholarly journals Spatio Temporal Distribution of Anthrax in Sulawesi 2015-2018

2020 ◽  
pp. 7-13
Author(s):  
Titis Furi Djatmikowati ◽  
Dini Wahyu Yudianingtyas ◽  
Haeriah Haeriah
Keyword(s):  
Information System ◽  
Spatial Distribution ◽  
Geographic Information System ◽  
Rainy Season ◽  
Endemic Area ◽  
Temporal Distribution ◽  
Risk Area ◽  
Epidemic Curve ◽  
South Sulawesi ◽  
Spatio Temporal

Three among five Provinces (South Sulawesi, West Sulawesi and Gorontalo) in Sulawesi island, Indonesia are endemic area of anthrax disease. The aim of this study was to describe the dynamic of anthrax during 2015-2018 and identified risk area in Sulawesi. We determined case of anthrax disease from passive-active surveillance data Disease Investigation Center Maros (DIC Maros) during 2015-2018. Spatial distribution describe by mapping using Quantum Geographic Information System (QGIS), the temporal distribution describe using epidemic curve and we calculated the proportion of animal infected of anthrax. There were thirty-three cases of anthrax spreaded into three Provinces in Sulawesi, there were twenty one cases in South Sulawesi (63.6%), nine cases in Gorontalo (27.3%) and three cases West Sulawesi (9.1%). There were eleven cases (33.3%) in 2015, fifteen cases (45.5%) in 2016, four cases (12%) in 2017 and three cases (6%) in 2018. Anthrax occured respectively in dry season in South Sulawesi and Gorontalo, different with West Sulawesi anthrax occured in rainy season. The proportion of the animal infected were 87% in cattle, 7% in horse, 3% goat and 3% in deer. Vaccination of anthrax in South Sulawesi and Gorontalo should be conducted in May; in Polewali Mandar, West Sulawesi in Februari.

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