Presentation for the SkyClaim - Fieldview integration showcase
by Dr. Cassidy Rankine, co-founder and co-creator of SkyClaim
More info at www.skyclaim.io
Introducing SkyClaim by Skymatics
Provides an overview of the background and motivation for the SkyClaim web application which utilizes aerial imagery information from consumer drones for crop insurance claims.
http://skymatics.com/skyclaim/
A presentation by Dr. Cassidy Rankine at the 2016 Farm Forum Event (Trimble and Agri-Trend) in Calgary Alberta, Dec 6-8 2016.
Drones can be used for various applications in agriculture like monitoring farms, operations, and protection. For monitoring, drones capture images and video that are transmitted to a ground station and then to a cloud-based processing center to produce prescriptions for tasks like fertilizing. Drones can monitor farms using intelligent cameras, multispectral sensors, thermal imaging, and laser scanners. They can also be used for operations like targeting fertilizer and pesticide application precisely. Drones help with protection by identifying wildlife that could damage crops. Some advantages of drones include lower costs compared to traditional methods, flexibility to work in different environments, and increased safety over manned aircraft operations.
Use of Drone for Efficient Water Management – A Case Study of Crop Assessmentpravinkolhe
Drone in water management, Unmanned Aerial Vehicles, Information& Communication Technology, Crop Area Measurement, image processing, orthomossaic image
This document discusses the use of agricultural drones and their various sensor technologies. It describes how visual, multispectral, thermal, LIDAR and hyperspectral sensors can be used for tasks like aerial mapping, plant health monitoring, livestock detection and precision agriculture. Examples are given of drone applications like chemical spraying, crop scouting and inventory management. The document also notes challenges for agricultural drones, such as limited battery life and the need for reliable data networks to download drone images and videos.
Remote sensing with drones: The challenges of obtaining truly quantitative da...ARDC
We develop Unmanned Aircraft Systems (UAS) and image processing techniques for environmental, agricultural, and high-precision aerial mapping applications
Our focus is on quantitative remote sensing of vegetation with the use of sophisticated UAS sensors to better understand the structure, distribution, and functioning of vegetation, and to bridge the observational scale gap between field samples and satellite observations.
Drones-as-a-Service for agricultural applications (by Philipp Trénel)TUS Expo
At TUS Nordics 2017, Philipp Trénel gave the presentation ‘Drones-as-a-Service for agricultural applications’ in our Arctic track, on Thursday 12 October 2017.
How are drones used for farming? The use of drones in agriculture is the future. Heavy lift drones capable of crop dusting and drones equipped with multispectral sensors will change the way in which farming is done.
Introducing SkyClaim by Skymatics
Provides an overview of the background and motivation for the SkyClaim web application which utilizes aerial imagery information from consumer drones for crop insurance claims.
http://skymatics.com/skyclaim/
A presentation by Dr. Cassidy Rankine at the 2016 Farm Forum Event (Trimble and Agri-Trend) in Calgary Alberta, Dec 6-8 2016.
Drones can be used for various applications in agriculture like monitoring farms, operations, and protection. For monitoring, drones capture images and video that are transmitted to a ground station and then to a cloud-based processing center to produce prescriptions for tasks like fertilizing. Drones can monitor farms using intelligent cameras, multispectral sensors, thermal imaging, and laser scanners. They can also be used for operations like targeting fertilizer and pesticide application precisely. Drones help with protection by identifying wildlife that could damage crops. Some advantages of drones include lower costs compared to traditional methods, flexibility to work in different environments, and increased safety over manned aircraft operations.
Use of Drone for Efficient Water Management – A Case Study of Crop Assessmentpravinkolhe
Drone in water management, Unmanned Aerial Vehicles, Information& Communication Technology, Crop Area Measurement, image processing, orthomossaic image
This document discusses the use of agricultural drones and their various sensor technologies. It describes how visual, multispectral, thermal, LIDAR and hyperspectral sensors can be used for tasks like aerial mapping, plant health monitoring, livestock detection and precision agriculture. Examples are given of drone applications like chemical spraying, crop scouting and inventory management. The document also notes challenges for agricultural drones, such as limited battery life and the need for reliable data networks to download drone images and videos.
Remote sensing with drones: The challenges of obtaining truly quantitative da...ARDC
We develop Unmanned Aircraft Systems (UAS) and image processing techniques for environmental, agricultural, and high-precision aerial mapping applications
Our focus is on quantitative remote sensing of vegetation with the use of sophisticated UAS sensors to better understand the structure, distribution, and functioning of vegetation, and to bridge the observational scale gap between field samples and satellite observations.
Drones-as-a-Service for agricultural applications (by Philipp Trénel)TUS Expo
At TUS Nordics 2017, Philipp Trénel gave the presentation ‘Drones-as-a-Service for agricultural applications’ in our Arctic track, on Thursday 12 October 2017.
How are drones used for farming? The use of drones in agriculture is the future. Heavy lift drones capable of crop dusting and drones equipped with multispectral sensors will change the way in which farming is done.
Multispectral camera sensors on agricultural drones can capture visible and infrared images of crops to help farmers more effectively manage their fields. Specialized software analyzes the imagery to produce data on soil properties, crop health, and yield estimates. This allows farmers to monitor their fields, detect issues, and optimize fertilizer and pesticide use to improve crop production while reducing costs and environmental impact. Common multispectral bands analyzed include red, green, red-edge, and near-infrared wavelengths. Several datasets captured with drones are provided as examples.
Choosing the Best UAV Drones for Precision Agriculture and Smart Farming: Agr...Redmond R. Shamshiri
Best Drones For Agriculture, Exploring agricultural drones, Agricultural Drone Technology, Agricultural Drones for Sale, Choosing the Best UAV Drones for Precision Agriculture and Smart Farming: Agricultural drone buyer’s guide for farmers and agriculture service professionals
Quadcopter based pesticide spraying systemAbhijith M.B
This document discusses the development of a quadcopter system for spraying pesticides in agricultural fields. It aims to reduce the health risks to farmers from direct exposure to pesticides while also allowing for more efficient spraying over large areas. The quadcopter is designed to autonomously spray pesticides using a preset path and can cover a large area in a short time. This system could help increase agricultural production to meet growing global food demands while improving safety for farmers compared to manual pesticide spraying methods. Precision agriculture using such automated technologies is presented as a way to enhance crop yields.
Farm drones have the potential to help farmers in three key ways: 1) They can spot disease and other problems in crops faster than traditional scouting methods, 2) They can help farmers use less chemicals, water, and other inputs by precisely applying them only where needed, saving money and reducing environmental impact, and 3) They provide data that allows farms to improve productivity through more efficient "closed-loop farming" practices. Drones are especially well-suited for agricultural use because farms typically involve large areas of private land where drones can safely operate under 400 feet and within visual line of sight of the operator.
Agricultural drones can help farmers work more efficiently and save time and money. They can monitor crop health, precisely spray pesticides and fertilizers over large fields in a short period, and analyze soil conditions. Some key benefits of agricultural drones include reducing waste and costs, saving water, increasing yields, and protecting farmers' health. They also help promote environmental sustainability by decreasing pollution from agricultural chemicals. Overall, the document argues that agricultural drones have great potential to improve productivity and transform the agriculture industry for economic and environmental benefits.
Fly Dragon Drone Tech presents their drone spraying system as an innovative solution for precision agriculture. Their drone uses an intelligent flight controller and precision spraying system to apply chemicals accurately. It has advantages over traditional spraying methods like backpacks or tractors in utilizing less pesticides, adapting to difficult terrain, and improving worker safety. The company argues drone spraying can benefit farmers through higher efficiency, lower costs, and reduced environmental impacts compared to conventional spraying.
This is based on a research study on the application of drone technology in India and showcase the benefits of its applicability to the agricultural sector in rendering services which in the past tends to be very tedious in executing.
Unmanned ariel vehicles(uav) in agricultureyogi1296
This document discusses the use of drones, or unmanned aerial vehicles, in agriculture. It provides details on how agricultural drones are used to help increase crop production and monitor crop growth through advanced sensors and imaging. Examples are given of various countries and organizations using drones to collect data on crop health, implement precision farming techniques, and assess crop damage. The agricultural drone market is predicted to significantly grow in the coming years as the technology allows for yield monitoring, remote sensing, variable rate applications, and more.
This document discusses using drones for early pest detection in crops. It notes that crop losses due to pests, diseases and weeds can range from 10-30% of production. Currently, detection requires time-consuming direct observation which can vary in accuracy. The document proposes using low-cost drones equipped with color sensors to periodically image individual plants and detect changes in color that could indicate infestation. The drone would send images to local supervisors who could then identify affected areas of the crop early on. Benefits of this system include avoiding significant crop losses and making use of technologies like IoT, smartphones, Raspberry Pi and related hardware and software.
Smart Copter is similar to a quad copter that consists of multiple features
Quadcopter or quad rotor aircraft is one of the UAV that is major focuses of active researches in recent years
This project involves a automatic sensor based system
Fundamental Research on Unmanned Aerial Vehicles to Support Precision Agricul...Redmond R. Shamshiri
Unmanned aerial vehicles carrying multimodal sensors for precision agriculture (PA) applications face adaptation challenges to satisfy reliability, accuracy, and timeliness. Unlike ground platforms, UAV/drones are subjected to additional considerations such as payload, flight time, stabilization, autonomous missions, and external disturbances. For instance, in oil palm plantations (OPP), accruing high resolution images to generate multidimensional maps necessitates lower altitude mission flights with greater stability. This chapter addresses various UAV-based smart farming and PA solutions for OPP including health assessment and disease detection, pest monitoring, yield estimation, creation of virtual plantations, and dynamic Web-mapping. Stabilization of UAVs was discussed as one of the key factors for acquiring high quality aerial images. For this purpose, a case study was presented on stabilizing a fixed-wing Osprey drone crop surveillance that can be adapted as a remote sensing research platform. The objective was to design three controllers (including PID, LQR with full state feedback, and LQR plus observer) to improve the automatic flight mission. Dynamic equations were decoupled into lateral and longitudinal directions, where the longitudinal dynamics were modeled as a fourth order two-inputs-two-outputs system. State variables were defined as velocity, angle of attack, pitch rate, and pitch angle, all assumed to be available to the controller. A special case was considered in which only velocity and pitch rate were measurable. The control objective was to stabilize the system for a velocity step input of 10m/s. The performance of noise effects, model error, and complementary sensitivity was analyzed.
Drones could deliver medications and supplies to patients being cared for in the home instead of a hospital-based setting. The future will see more outpatient care and even home-based care that used to be delivered in the hospital.
Smart Management of Oil Palm Plantations with Autonomous UAV Imagery and Robu...Redmond R. Shamshiri
Redmond Shamshiri proposes using unmanned aerial vehicles (UAVs) equipped with various sensors to conduct precision agriculture tasks in oil palm plantations. Some key applications discussed include automated palm tree inventory and measurements, yield mapping, and assessing tree health and growth. The goals are to develop systems for smart inventory management and health assessment that can autonomously process image data and make management decisions. This would allow plantations to be monitored at a higher resolution and in more detail than previously possible.
CANEFIT solution is a unique toolbox driven by
agronomic insights and developed by GAMAYA to address
the specific needs of sugarcane cultivation in Brazil.
GPS and GIS are used together to collect and analyze spatial data. GPS is a satellite system that provides location data, while GIS is software that stores and manipulates spatial data from multiple sources and allows users to generate layered maps. An example is an agricultural producer using a GPS receiver to locate a water source and then combining that point data in a GIS with soil maps, aerial imagery and other data to generate customized field maps. GIS information and maps have various uses for agricultural planning and biosecurity management.
CAA approved drone pilots are playing an increasingly important role in worldwide agriculture. Against a backdrop of a growing world population, faced with the challenge of sustaining food production with dwindling resources, drones can offer a reasonably priced precision farming solution.
Automated Catastrophic Events Geographic data load using FME PlatformConsortech
The document discusses how Guy Carpenter uses FME to automate the integration of geographic data on catastrophic events into its risk analysis platform. It loads data from various sources on hurricanes, earthquakes, wildfires, and other perils and transforms it into usable formats. This allows for pre-event planning and post-event response like claims validation. FME enables scheduling automated data feeds and validating the loads. The platform provides exposure analysis, event monitoring, and underwriting support through access to live and historical event footprints.
Drone technology has left a long-lasting impact on the Agriculture industry of India and its efficiency. We present drone-powered solutions to farmers to increase productivity in crop monitoring to planting, Livestock Management, Pesticide Spraying, Crop Stress identification, Treatment Planning, Plant Growth Monitoring, Precision Farming, Scouting and much more.
We use high-tech Aerial Surveying drones equipped with advanced sensors, such as RGB and Multispectral Sensors , to procure precise data. Drones such as DJI Inspire 2 accumulate high-resolution crop data to identify any issues with the crops and notify them for immediate action before damage occurs. Geo-tagging Aerial Images provide valuable information that reduces cost and boosts yield by a significant percentage.
The document describes an AI system for flood forecasting using multiple agents. The system includes agents for a hydrology database, collecting flood-related variables, sending notifications, managing a virtual emergency operations center, and generating reports. The performance is measured based on safety, timeliness, location accuracy, message clarity, and risk reduction. The environment involves factors like storms, weather, temperature, water levels, and is deterministic, dynamic, multi-agent, and continuous. The system aims to improve flood forecasting accuracy and lead times to help governments and disaster management agencies issue more effective warnings.
Multispectral camera sensors on agricultural drones can capture visible and infrared images of crops to help farmers more effectively manage their fields. Specialized software analyzes the imagery to produce data on soil properties, crop health, and yield estimates. This allows farmers to monitor their fields, detect issues, and optimize fertilizer and pesticide use to improve crop production while reducing costs and environmental impact. Common multispectral bands analyzed include red, green, red-edge, and near-infrared wavelengths. Several datasets captured with drones are provided as examples.
Choosing the Best UAV Drones for Precision Agriculture and Smart Farming: Agr...Redmond R. Shamshiri
Best Drones For Agriculture, Exploring agricultural drones, Agricultural Drone Technology, Agricultural Drones for Sale, Choosing the Best UAV Drones for Precision Agriculture and Smart Farming: Agricultural drone buyer’s guide for farmers and agriculture service professionals
Quadcopter based pesticide spraying systemAbhijith M.B
This document discusses the development of a quadcopter system for spraying pesticides in agricultural fields. It aims to reduce the health risks to farmers from direct exposure to pesticides while also allowing for more efficient spraying over large areas. The quadcopter is designed to autonomously spray pesticides using a preset path and can cover a large area in a short time. This system could help increase agricultural production to meet growing global food demands while improving safety for farmers compared to manual pesticide spraying methods. Precision agriculture using such automated technologies is presented as a way to enhance crop yields.
Farm drones have the potential to help farmers in three key ways: 1) They can spot disease and other problems in crops faster than traditional scouting methods, 2) They can help farmers use less chemicals, water, and other inputs by precisely applying them only where needed, saving money and reducing environmental impact, and 3) They provide data that allows farms to improve productivity through more efficient "closed-loop farming" practices. Drones are especially well-suited for agricultural use because farms typically involve large areas of private land where drones can safely operate under 400 feet and within visual line of sight of the operator.
Agricultural drones can help farmers work more efficiently and save time and money. They can monitor crop health, precisely spray pesticides and fertilizers over large fields in a short period, and analyze soil conditions. Some key benefits of agricultural drones include reducing waste and costs, saving water, increasing yields, and protecting farmers' health. They also help promote environmental sustainability by decreasing pollution from agricultural chemicals. Overall, the document argues that agricultural drones have great potential to improve productivity and transform the agriculture industry for economic and environmental benefits.
Fly Dragon Drone Tech presents their drone spraying system as an innovative solution for precision agriculture. Their drone uses an intelligent flight controller and precision spraying system to apply chemicals accurately. It has advantages over traditional spraying methods like backpacks or tractors in utilizing less pesticides, adapting to difficult terrain, and improving worker safety. The company argues drone spraying can benefit farmers through higher efficiency, lower costs, and reduced environmental impacts compared to conventional spraying.
This is based on a research study on the application of drone technology in India and showcase the benefits of its applicability to the agricultural sector in rendering services which in the past tends to be very tedious in executing.
Unmanned ariel vehicles(uav) in agricultureyogi1296
This document discusses the use of drones, or unmanned aerial vehicles, in agriculture. It provides details on how agricultural drones are used to help increase crop production and monitor crop growth through advanced sensors and imaging. Examples are given of various countries and organizations using drones to collect data on crop health, implement precision farming techniques, and assess crop damage. The agricultural drone market is predicted to significantly grow in the coming years as the technology allows for yield monitoring, remote sensing, variable rate applications, and more.
This document discusses using drones for early pest detection in crops. It notes that crop losses due to pests, diseases and weeds can range from 10-30% of production. Currently, detection requires time-consuming direct observation which can vary in accuracy. The document proposes using low-cost drones equipped with color sensors to periodically image individual plants and detect changes in color that could indicate infestation. The drone would send images to local supervisors who could then identify affected areas of the crop early on. Benefits of this system include avoiding significant crop losses and making use of technologies like IoT, smartphones, Raspberry Pi and related hardware and software.
Smart Copter is similar to a quad copter that consists of multiple features
Quadcopter or quad rotor aircraft is one of the UAV that is major focuses of active researches in recent years
This project involves a automatic sensor based system
Fundamental Research on Unmanned Aerial Vehicles to Support Precision Agricul...Redmond R. Shamshiri
Unmanned aerial vehicles carrying multimodal sensors for precision agriculture (PA) applications face adaptation challenges to satisfy reliability, accuracy, and timeliness. Unlike ground platforms, UAV/drones are subjected to additional considerations such as payload, flight time, stabilization, autonomous missions, and external disturbances. For instance, in oil palm plantations (OPP), accruing high resolution images to generate multidimensional maps necessitates lower altitude mission flights with greater stability. This chapter addresses various UAV-based smart farming and PA solutions for OPP including health assessment and disease detection, pest monitoring, yield estimation, creation of virtual plantations, and dynamic Web-mapping. Stabilization of UAVs was discussed as one of the key factors for acquiring high quality aerial images. For this purpose, a case study was presented on stabilizing a fixed-wing Osprey drone crop surveillance that can be adapted as a remote sensing research platform. The objective was to design three controllers (including PID, LQR with full state feedback, and LQR plus observer) to improve the automatic flight mission. Dynamic equations were decoupled into lateral and longitudinal directions, where the longitudinal dynamics were modeled as a fourth order two-inputs-two-outputs system. State variables were defined as velocity, angle of attack, pitch rate, and pitch angle, all assumed to be available to the controller. A special case was considered in which only velocity and pitch rate were measurable. The control objective was to stabilize the system for a velocity step input of 10m/s. The performance of noise effects, model error, and complementary sensitivity was analyzed.
Drones could deliver medications and supplies to patients being cared for in the home instead of a hospital-based setting. The future will see more outpatient care and even home-based care that used to be delivered in the hospital.
Smart Management of Oil Palm Plantations with Autonomous UAV Imagery and Robu...Redmond R. Shamshiri
Redmond Shamshiri proposes using unmanned aerial vehicles (UAVs) equipped with various sensors to conduct precision agriculture tasks in oil palm plantations. Some key applications discussed include automated palm tree inventory and measurements, yield mapping, and assessing tree health and growth. The goals are to develop systems for smart inventory management and health assessment that can autonomously process image data and make management decisions. This would allow plantations to be monitored at a higher resolution and in more detail than previously possible.
CANEFIT solution is a unique toolbox driven by
agronomic insights and developed by GAMAYA to address
the specific needs of sugarcane cultivation in Brazil.
GPS and GIS are used together to collect and analyze spatial data. GPS is a satellite system that provides location data, while GIS is software that stores and manipulates spatial data from multiple sources and allows users to generate layered maps. An example is an agricultural producer using a GPS receiver to locate a water source and then combining that point data in a GIS with soil maps, aerial imagery and other data to generate customized field maps. GIS information and maps have various uses for agricultural planning and biosecurity management.
CAA approved drone pilots are playing an increasingly important role in worldwide agriculture. Against a backdrop of a growing world population, faced with the challenge of sustaining food production with dwindling resources, drones can offer a reasonably priced precision farming solution.
Automated Catastrophic Events Geographic data load using FME PlatformConsortech
The document discusses how Guy Carpenter uses FME to automate the integration of geographic data on catastrophic events into its risk analysis platform. It loads data from various sources on hurricanes, earthquakes, wildfires, and other perils and transforms it into usable formats. This allows for pre-event planning and post-event response like claims validation. FME enables scheduling automated data feeds and validating the loads. The platform provides exposure analysis, event monitoring, and underwriting support through access to live and historical event footprints.
Drone technology has left a long-lasting impact on the Agriculture industry of India and its efficiency. We present drone-powered solutions to farmers to increase productivity in crop monitoring to planting, Livestock Management, Pesticide Spraying, Crop Stress identification, Treatment Planning, Plant Growth Monitoring, Precision Farming, Scouting and much more.
We use high-tech Aerial Surveying drones equipped with advanced sensors, such as RGB and Multispectral Sensors , to procure precise data. Drones such as DJI Inspire 2 accumulate high-resolution crop data to identify any issues with the crops and notify them for immediate action before damage occurs. Geo-tagging Aerial Images provide valuable information that reduces cost and boosts yield by a significant percentage.
The document describes an AI system for flood forecasting using multiple agents. The system includes agents for a hydrology database, collecting flood-related variables, sending notifications, managing a virtual emergency operations center, and generating reports. The performance is measured based on safety, timeliness, location accuracy, message clarity, and risk reduction. The environment involves factors like storms, weather, temperature, water levels, and is deterministic, dynamic, multi-agent, and continuous. The system aims to improve flood forecasting accuracy and lead times to help governments and disaster management agencies issue more effective warnings.
Using Remote Sensing Data to Develop Catastrophe ModelsChris Ewing
Information on how Impact Forecasting are using Remote Sensing data to develop catastrophe models. Presented at Lloyd's Old Library on Friday 16th September 2016 at the AGI and RSPSoc event "Satellite remote sensing for disaster risk reduction and insurance".
Reduction in fraudulent crop insurance claims using drone technologyVarun Mittal
This solution protects insurers against fraudulent crop insurance claims with drone technology that is able to capture data to predict yields of crops with high levels of accuracy as well as reduce turn-around time in case of farm flooding.
Cropp (Coltures Risks Observation and Prevention Platform)Mohamed Elhariry
CROPP is a platform designed to help farmers monitor their crops and lands using an Android app and website. The app allows farmers to check field status, send feedback to other growers, and access satellite images of their selected crops. The website allows farmers to create accounts and manage their lands. Future developments include extending system monitoring to multiple insects and species, providing precise data to biologists to predict disease evolution, and accessing finer satellite images to monitor crops and lands.
The document discusses risk management and provides information on various aspects of conducting risk assessments. It begins with defining risk and explaining risk management. It then outlines the steps to conduct a risk assessment, which includes identifying threat sources and events, consequences, assessing single loss expectancies, likelihoods, and deriving risk values.
It also discusses developing and evaluating risk control options, with categories like risk acceptance, avoidance, reduction and transfer. The process involves assessing costs of options and their effectiveness in reducing risk. A cost-benefit analysis is done to determine the most cost-effective options.
The risk management framework also includes phases like risk reporting, management review and decision making, implementation of selected controls, and ongoing monitoring and control of risks
Dronxt the Era evolution is formed with a vision of creating new evolution in Intel and super inhuman effectiveness. it aims to enhance growth of drone’s sector globally in manufacturing innovative technology in both aerial unmanned and under water drones.
This document describes the development of a GIS service using CloudEO Platform data and tools to visualize areas in El Salvador that have a higher susceptibility to landslides based on slope, rainfall data, and historical landslide events, with the goal of providing early warning systems that are accessible via mobile, desktop, and web applications. The process involves collecting and interpolating rainfall observations, reclassifying the data according to warning levels, and intersecting it with pre-generated slope data to identify at-risk areas. Screenshots from the service show maps highlighting susceptible regions based on real-time rainfall observations.
Using Data Integration to Deliver Intelligence to Anyone, AnywhereSafe Software
Data integration makes it possible to deliver intelligence and keep decision makers, first responders, and civilians informed. For over 20 years, FME has been trusted by federal governments to move data from nearly any source to the target destination, while saving time and budget resources.
With FME, federal governments can deliver open data, improve emergency & disaster response, enhance land management, turn public safety and defense into actionable results, and integrate & deliver location intelligence.
Networking smartphones for disaster recovery using teamphoneIJARIIT
In this paper, we examine how to use networks with smartphones for providing communications in disaster recovery.
By lessening the communication gap among different kinds of wireless networks, we have designed and implemented a system
called TeamPhone, which provides Android phones the capabilities on communications in disaster helper. TeamPhone
consists of two components: a messaging system between rescue worker and the victim and a self-rescue system. The
messaging system between rescue worker and victim integrates cellular networking, ad-hoc networking, and opportunistic
networking seamlessly, and enables proper communication. The self-rescue system finds different communication network
ways for trapped survivors. Such a group of Android phones can cooperatively get a notification and send out emergency
messages in an energy-efficient manner with their location and position information so as to help rescue operations. We have
implemented TeamPhone as a prototype application on the Android platform and deployed it on all types of smartphones from
Samsung to Redmi and others. Results demonstrate that TeamPhone can properly enhance communication requirements and
increase the pace of disaster recovery. We are creating three applications with a centralized cloud for communication. First for
the admin who will monitor victim and rescue worker on Google map and other two for rescue worker and disaster victim.
The document summarizes statistics from the Cropwise digital farming solution in 2021. It states that 12.4 million hectares of new fields were added, over double the previous year. 1.19 million agricultural operations and 643,268 scouting reports were added, increases of 82% and 20% respectively over the prior year. The system also tracked over 2.4 million photos, 146,557 machinery units, and 3.8 million tasks. Cropwise saw a 1.5 times increase in alerts created. 243 new weather stations also joined. The solution provides multispectral satellite data including NDVI indexes at various resolutions, as well as visual images to analyze field conditions. Image comparison and overlay tools are available. Crop
This document proposes a weather-based decision support application to help farmers with crop protection, monitoring, and cost optimization. It would generate early alerts for diseases and pests specific to crops like grapes. Sensors in automated weather stations would monitor temperature, humidity, wind, rainfall, and solar conditions. Forecasts up to 7 days in advance would integrate with a GIS-based interface to map risks at different crop stages. Decision support information and alerts would disseminate via web, SMS, voice broadcasts, and a mobile app to help farmers make informed decisions. Insurance templates could also be customized based on location-specific crop risks and weather influences.
Niruthi provides agricultural insurance and ensures food security using technology. It collects weather data from satellites and sensors, monitors crop growth, and provides yield assessments. Its systems offer location-specific climate data, crop forecasts, and expert alerts. This helps insurance providers offer affordable coverage scaled to individual farms.
I-REACT is an EU-funded project that aims to improve emergency management of natural hazards through new technologies. It will integrate data from multiple sources like social media, satellites, and weather forecasts to create risk maps and early warning systems. Key technologies include mobile apps, augmented reality glasses, drones, and a decision support system. The project seeks to involve citizens, first responders, and authorities to better prevent, prepare for, and respond to disasters throughout their phases. Field tests will take place in several European countries.
This document discusses using artificial intelligence and satellite imagery to identify natural disasters. It proposes comparing pixel values in bi-temporal (two-time period) satellite images from before and after a disaster to detect changes indicating damage. A change detection model would analyze satellite images captured over time of a specific area to identify variability indicating a disaster occurrence. Deep learning models could then be trained on these change maps to automatically detect and classify disaster types and affected areas for faster disaster assessment and relief coordination.
Disaster management using Remote sensing and GISHarsh Singh
The document discusses the roles of remote sensing and GIS in disaster management. It provides definitions of disaster and disaster management. GIS and remote sensing help in all phases of disaster management including planning, mitigation, preparedness, response and recovery. Specific examples are given of how they assist with cyclones, floods and droughts. A case study is summarized showing how GIS was used to generate maps to help manage flooding in a district in India.
project on pneumonia detection using machine learning ppt 2.pdfKarthi996505
This project aims to develop an intelligent system for earthquake prediction using machine learning models. The system will be trained on a dataset containing records of 782 past earthquakes from 2001 to 2023, including attributes like magnitude, date, location, and intensity. It will evaluate different algorithms on a test set to identify the best-performing model for predicting future earthquakes. The model could help save lives and reduce damage by providing more accurate earthquake forecasts.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
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The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
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2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Fueling AI with Great Data with Airbyte WebinarZilliz
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Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...Tatiana Kojar
Skybuffer AI, built on the robust SAP Business Technology Platform (SAP BTP), is the latest and most advanced version of our AI development, reaffirming our commitment to delivering top-tier AI solutions. Skybuffer AI harnesses all the innovative capabilities of the SAP BTP in the AI domain, from Conversational AI to cutting-edge Generative AI and Retrieval-Augmented Generation (RAG). It also helps SAP customers safeguard their investments into SAP Conversational AI and ensure a seamless, one-click transition to SAP Business AI.
With Skybuffer AI, various AI models can be integrated into a single communication channel such as Microsoft Teams. This integration empowers business users with insights drawn from SAP backend systems, enterprise documents, and the expansive knowledge of Generative AI. And the best part of it is that it is all managed through our intuitive no-code Action Server interface, requiring no extensive coding knowledge and making the advanced AI accessible to more users.
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When it comes to unit testing in the .NET ecosystem, developers have a wide range of options available. Among the most popular choices are NUnit, XUnit, and MSTest. These unit testing frameworks provide essential tools and features to help ensure the quality and reliability of code. However, understanding the differences between these frameworks is crucial for selecting the most suitable one for your projects.
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...alexjohnson7307
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Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
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Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
2. SKYMATICS – who we are
We are remote sensing engineers, geomatics experts, big data
scientists, AI developers, and unmanned technology enthusiasts
Focused on simplifying big data image analysis challenges
3. Why map your field with a drone?
A. Precision Agriculture
> Variable Rate Application maps
B. Crop Scouting / Spot Checking
> Weeds, Disease and Pest management
C. Disaster and Loss Management
> Severe weather, wildlife, machinery failure, etc
4. Using drones after disasters…
Fast and effective to
spot damage areas
from the air….
but challenging to
measure the exact
losses
5. The SkyClaim App by Skymatics
What is SkyClaim?
An online application that
identifies, measures and
reports crop loss areas using
high definition aerial imagery.
Designed to simplify complex &
tedious image analysis tasks to
evaluate crop disturbances
Example SkyClaim Crop Damage Analysis Report
7. SkyClaim uses AI to find damages
In addition to using combinations of vegetation indices
we use advanced object-based image analyses
Enables higher level feature extraction and
crop damage classification accuracy
8. Combine Layers of Image Information
Extracting spatial,
spectral, and
structural plant
information from
layers of image data
significantly improves
our accuracy and sets
us apart from other
image processing
approaches
9. Unproductive areas all look the same using vegetation
index maps - hard to differentiate cause of stress/dieback
Beyond Greenness Indices
RGB
10. Using computer vision to identify non-crop features
Semantic segmentation used to classify all components of the scene
23. Reviews:
what people are saying
“Having a report with a breakdown of damage,
especially widespread damage, is huge…
“When you are talking about this amount of
money that is going to be paid out or not paid
out, I tell people, ‘if your insurance agent
doesn’t provide you with something like this,
you should be providing it for yourself!’ ”
- Jeremy Jones
Overhead Ag, Illinois
24. Integrating SkyClaim with Climate FieldView
● Phase 1 – Share Field Boundaries – Late August 2018
○ Import your field boundaries from FieldView to SkyClaim to constrain damage analysis
● Phase 2 – Damage Analysis in FieldView – Early 2019
○ Run a SkyClaim Crop Damage Analysis and generate Reports for qualified imagery in your
FieldView account
○
● Phase 3 – Field Data Integration – Mid 2019
○ Leverage Your FieldView Production Data for high accuracy loss assesment