This document summarizes SuperMap's meteorological forecasting and risk management software solutions. It describes modules for meteorological disaster risk management, emergency warning information release, agrometeorological intelligent services, and fine mesh forecasts. The software includes subsystems for objective forecast generation, product processing and sharing, forecast editing and correction, prediction inspection, and data storage. It provides functions for monitoring, early warning, product release, data analysis and display on maps and charts. The system aims to help manage meteorological disasters and support agrometeorological services.
TSO Reliability Management: a probabilistic approach for better balance betwe...Leonardo ENERGY
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The webinar will present the methodology developed, its application to real time operation, and the overall benefits of such probabilistic approach. A 2nd webinar will be planned to present the test results of applying GARPUR methodology to asset management and system development.
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The main objective of this talk is to show how you can extend an Icinga2 active monitoring with a passive monitoring engine.
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5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
Nowadays, weather consider the important component in many domains so, these domains use weather station to measure the parameters of weather through embedded sensors and view the measurements by using monitoring system which allow the user to make analysis about an obtained data of the weather Our work based on usage of weather station to measure certain parameters which effect on our telescope (mirror) which responsible for orbs vision in the space, and view the measurements through monitoring system to make analysis about these measurements to control closing and opening operations of shutter of the building and telescope
( mirror)in this building . These operations can operate by building expert system by using EXsys corvid software program and that system like human expertise through usage of knowledge base and inference engine .
Modernizing Hazard Data Feeds at the PDCSafe Software
In this presentation, we will highlight how moving from a custom build-in-house solution for aggregating data feeds to using FME Server and Desktop helped to support disaster risk reduction efforts.
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The webinar will cover a range of topics: including flood, fire, heat, drought, population health, and critical infrastructure, among others. We will also highlight our partner and customer experiences in this field and present key results from our participation in recent OGC pilots on Climate Resilience and Disaster Response. We will also be joined by special guests sharing their experience in the AgriTech sector, where gathering metrics and data from sensors is helping to reduce the demand from farming on precious resources like water for irrigation.
Through live demos, attendees will gain practical knowledge in accessing climate services from USGS & Environment Canada and how to convert climate model NetCDF outputs into more GIS-friendly formats like geodatabase & GeoJSON.
Finally, we will address the significant gaps and challenges that remain in assessing climate-related hazards and risks, and explore how FME can play a critical role in addressing these gaps. Join us for this important discussion on how you can use FME to build resilience and mitigate the impacts of climate change.
OSMC 2019 | Tornado – Extend Icinga2 for Active and passive Monitoring of com...NETWAYS
The main objective of this talk is to show how you can extend an Icinga2 active monitoring with a passive monitoring engine.
With Icinga2 you focus on active monitoring. With Tornado you can do exactly the opposite and focus on passive monitoring. You receive events from different channels like SNMP Trap, Syslog, Email and match them against a rule engine and decide which action to associate. A very common use case is to set a Icinga2 Service status (critical, warning, ok) based on a matched rule. In addition you could also subscribe the Icinga API Stream and define matching rules which you would like to correlate and associate an executor for example create a new entry in Elasticsearch. Another common use case could be to register Tornado as a webhook for example in Elasticsearch Watcher collect the alarms and set the status on a Icinga Service Check. During the talk I will explain why Tornado was built from Würth Phoenix in rust and what are the common use case we would like to address with it.
DroneLogbook Australia About Us Dec-2018Scott Hamey
DroneLogbook Australia is a subsidiary of DroneAnalytics a Swiss based company offering local Australian customer service and support.
DroneLogbook SaaS is hosted in Australia for the Australian commercial drone industry.
Euphoric solves all the cloud complexities and helps setup intelligent observability across cloud and hybrid environments with continuous auto-discovery of hosts, VMs, serverless, cloud services, containers and Kubernetes, devices, logs, events and more.
Euphoric proactively discovers cloud performance bottlenecks and quickly resolve them before they impact end users
Meteo Risk Response Presentation at International Disaster and Risk Conferenc...Global Risk Experts
5th International Disaster and Risk Conference in Davos Switzerland
Global Risk Experts, together with their JV Partners SwissNor and MeteoGroup, were participating and showcasing their new approach on managing weather related exposures to minimize flood and storm losses at the 5th International Disaster and Risk Conference. Over 800 participants from Academia, Governmental Agency and the private sector were participating.
5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
Nowadays, weather consider the important component in many domains so, these domains use weather station to measure the parameters of weather through embedded sensors and view the measurements by using monitoring system which allow the user to make analysis about an obtained data of the weather Our work based on usage of weather station to measure certain parameters which effect on our telescope (mirror) which responsible for orbs vision in the space, and view the measurements through monitoring system to make analysis about these measurements to control closing and opening operations of shutter of the building and telescope
( mirror)in this building . These operations can operate by building expert system by using EXsys corvid software program and that system like human expertise through usage of knowledge base and inference engine .
Modernizing Hazard Data Feeds at the PDCSafe Software
In this presentation, we will highlight how moving from a custom build-in-house solution for aggregating data feeds to using FME Server and Desktop helped to support disaster risk reduction efforts.
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Climate change affects us all. It is an urgent issue that requires practical solutions to mitigate its impacts. Data is at the center of understanding this challenge. In this informative webinar, we will explore how data can be leveraged to translate climate change projections into tangible hazard and risk assessments at the local level.
The webinar will cover a range of topics: including flood, fire, heat, drought, population health, and critical infrastructure, among others. We will also highlight our partner and customer experiences in this field and present key results from our participation in recent OGC pilots on Climate Resilience and Disaster Response. We will also be joined by special guests sharing their experience in the AgriTech sector, where gathering metrics and data from sensors is helping to reduce the demand from farming on precious resources like water for irrigation.
Through live demos, attendees will gain practical knowledge in accessing climate services from USGS & Environment Canada and how to convert climate model NetCDF outputs into more GIS-friendly formats like geodatabase & GeoJSON.
Finally, we will address the significant gaps and challenges that remain in assessing climate-related hazards and risks, and explore how FME can play a critical role in addressing these gaps. Join us for this important discussion on how you can use FME to build resilience and mitigate the impacts of climate change.
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2. P2
Meteorological disaster risk management
Release management of emergency warning
information
Agrometeorological intelligent service
Fine Mesh Forecast
3. P3
Meteorological disaster risk management
Release management of emergency warning
information
Agrometeorological intelligent service
Fine Mesh Forecast
4. P4
Disaster detection and monitoring for process, event and
impact
Disaster Monitoring and
Detection
Big Data Application Observation, census, forecast and simulation
Risk Zoning of Impact
Assessment
Carry out disaster risk zoning and industry-oriented impact
assessment
Inspection and Benefit
Evaluation
Inspection and evaluation of product quality and service effect
Risk warning and service Establishing risk early warning system and providing reliable
and timely services
Actively carry out research on risk transfer and sharingRisk Transfer and
Adaptation
14. P14
Assessment of
precipitation
resources
Big rivers
Depth departure
percentage of runoff
in tertiary watershed
Water regime
monitoring
Precipitation
resources in the
upper reaches of
the reservoir
Runoff of ten
basins departure
VIC streamflow
Runoff of tertiary
river basin
departure
Departure
percentage of
runoff depth of
ten basins
Reservoir water
regime
Runoff depth of
tertiary river
basin
Runoff depth of
ten basins
Water resources
assessment
Runoff of tertiary
river basin
Runoff of ten
basins
15. P15
Runoff Depth of Ten BasinsRiver Basin Runoff Depth
VIC Streamflow Big Rivers
20. P20
Meteorological disaster risk management
Release management of emergency warning
information
Agrometeorological intelligent service
Fine Mesh Forecast
21. P21
Emergency warning information release system
Hardware infrastructure constructionConstruction of early warning release
center
Database system
construction
Construction of early
warning application
system
Information release
channel construction
Data access interface Data exchange and sharing Data management
Early warning information
release management
system
Monitoring and feedback
evaluation system
Comprehensive research and
accurate release support system
Early warning business
duty system
Professional department data
management system
Application service system
Platform service
management system
Back-end management system
Mobile App Wechat
FaxMessage Email
Weibo
LED
Radio
12379 Website
Warning radio
Emergency broadcast
TV
Standard specification
production
Standard for making
early warning
information
Standard and
specification of
issuing means
Standard for business
process
Standard for storage
of early warning
information
24. P24
The automatic meteorological disaster
identification model is run in the background,
which is pushed forward through the message
middleware at a fixed time, such as high
temperature heat wave, low temperature
freezing injury, strong wind, dust, cold wave and
drought.
25. P25
Affected area, population,
GDP, hidden danger points of
medium and small rivers,
hidden danger points of
landslides, hidden danger
points of mountain torrents,
schools, hospitals, fire
bureaus, gas stations
26. P26
Emergency office, civil affairs,
public security, land, environment,
transportation, agriculture,
forestry, water conservancy,
health and Family Planning
Commission, tourism, safety
supervision, food and drug
supervision, meteorological and
earthquake departments and
bureaus
28. P28
p Evaluate whether the effect and result of early warning information release meet the expected
objectives
p Realize the whole process monitoring and channel link monitoring of alert publishing, including the
monitoring of alert information publishing quantity, distribution, region, department, channel, type
and other related information.
30. P30
Based on 3D GIS technology, display data on 3D terrain, correlate
relevant emergency plans, provide auxiliary support for on-site or
remote emergency command and decision-making, and effectively
handle major emergencies.
33. P33
Meteorological disaster risk management
Release management of emergency warning
information
Agrometeorological intelligent service
Fine Mesh Forecast
34. P34
Modern Agrometeorological Integrated Service Platform
Bacis Support Part(BSP)
Automatic
data
receiving
and sending
subsystem
Platform
operation
management
subsystem
Algorithm
model
running
subsystem
Interface
management
subsystem
Business Application Part
(BAP)
Monitoring
and early
warning
subsystem
Product
release
management
subsystem
Business
work
subsystem
Professional
data
acquisition
subsystem
Information Service
Part(ISP)
Web services
subsystem
Wechat
service
subsystem
Android
service
subsystem
Agrometeorological intelligent service
49. P49
Meteorological disaster risk management
Release management of emergency warning
information
Agrometeorological intelligent service
Fine Mesh Forecast
52. P52
Integrated objective prediction algorithm results
Feature Algorithm
Temperature MOS
Kalman filtering
Maximum and
minimum
temperature
Fitting method、MOS
Rainfall Probability matching average
method for optimal members
Relative Humidity Conversion method
Cloudiness Bilinear difference
Wind Bilinear difference
Visibility Bilinear difference
Thunder Neural network method
Objective Product Generator
53. P53
Region assignment,
Original value addition
and subtraction, Single
point modification、
Copy paste tool...
Trend correction,
extremum feedback,
temperature difference”
Magnitude
matching,Trend
correction,Drop zone
displacement
General
Tools
Rainfull
Tools
Temperatu
re Tools
Wind
Tools
Wind direction
correction, wind
speed correction
Edit Correction Subsystem
54. P54
It shows the ecthin high-
rise wind, which
provides the basis for the
correction.
Weather
analysis
Save or restore
modified data
Save and
restore
The map is divided
into many parts and
revised based on a
single block.
Zoning
correctio
n
Judge whether special
value occurs to elements;
judge whether logical
error occurs between
elements
Special
value
check
Edit Correction Subsystem
55. P55
Area assignment and original value addition and subtraction: drawing area assignment
Assign or add devaluation (temperature and precipitation ) to the current selection
Edit Correction Subsystem - Area Assignment
59. P59
Extremum feedback: adjust the whole point temperature between extremum
points by revising the maximum and low temperature (extremum).
60. P60
Before
Correction
After
Correction
Temperature trend correction: the lowest and highest temperature and the whole point
temperature are unified on a curve, and the whole point temperature can be adjusted by adjusting
the lowest and highest temperature. After adjustment, the temperature of other grid points in the
region has the same change trend
61. P61
Wind correction: using wind speed
magnitude to adjust wind speed
Wind correction: use the steering wheel to
adjust the wind direction
Edit Correction Subsystem - Wind Correction
62. P62
Weather analysis tools: display of main products of
numerical model; weather system can be marked to
help forecasters determine the landing area
Edit Correction subsystem - weather analysis tool
63. P63
All element multi time effective inspection Single element single time effect inspection
Special value check: judge whether the element has singular value; judge whether there is logical error between elements
Exception type prompt
Edit Correction Subsystem - Special Value Check