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Perceptual Informatics uses Azure Maps for their AI for Earth research
I had the opportunity to meet & chat with Ted Bradley and Bjorn Brooks of Perceptual Informatics today at the AI for Earth Summit at the Microsoft campus. Perceptual Informatics, an environmental startup company, has been awarded Microsoft's AI for Earth Grant to further its research on the economic effects of climate change on the agriculture industry. During our meeting, Ted Bradley talked about the work he was doing analyzing weather data and correlating to harvest data across multiple years. He also demoed the work he was doing using Azure Maps. Perceptual has selected Azure Maps as their Geospatial & Data Visualization platform and is doing some amazing work with it to identify the sustainability of short- and long-term agricultural investments and to determine costs and mitigate risks associated with climate change. Here is a link to a small example of their work (they have plenty of additional models including volatility and risk models) Historical Corn Viewer Read more about their work here.Azure Maps Covid-19 Open Source Project for Healthcare Agencies
John Snow’s Cholera map is generally regarded as the first attempt to use geospatial analytics to better understand patterns in the spread of a pandemic. His maps uncovered the cause of the Broad Street cholera outbreak of 1854 (and was part of the 1846–1860 cholera pandemic happening worldwide) in the Soho district of the City of Westminster, London. With the prevalence of data and mapping tools, its something that data journalists and healthcare organizations do on a regular basis to understand hidden patterns and causes of viral outbreaks. Today, COVID-19 is on our minds as the situation evolves across the globe. Many of us at Microsoft, are using our technology & innovative ideas to help address the many issues around dealing with the pandemic. The Azure Maps team is passionate about enabling our customers with geospatial insights: the ability to unlock interesting insights and patterns from combinations of publicly available data. In an attempt to empower healthcare agencies from around the world to easily use our geospatial capabilities, we decided to pull together a dashboard that analyzed the progression of the Covid-19 virus over time. Our goal is to enable, healthcare agencies & others to reuse the code that we built out, but use data sources of their choice, add local data, like for instance, nearby hospitals, capacity information, contacts and more. The dashboard can be customized for specific geographies and enhanced with proprietary and local information. The dashboard is designed for use for internal as well as external communication and reporting. We chose to make the source code available to healthcare agencies and others, specifically so that they can customize it for the information and KPIs that they want to track, analyze and communicate. We feel that healthcare professionals best understand the nuances in epidemiology and the calculations needed for getting the right insights. As a result, we made our platform & code available for them to quickly be up and running. We built out the dashboard by connecting to the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). The dashboard was setup to analyze the spatio temporal data available and animate the time series as the virus spread across the globe over time. We hope the source code is useful for healthcare agencies around the world who can focus on analyzing the data, understanding the patterns and making valuable decisions with it. You can download the source code from the GitHub repo: http://bit.ly/2QbfWk4 For more information about Azure Maps: Overview: https://azure.com/maps Documentation: https://aka.ms/AzureMapsDocs Getting Started: https://aka.ms/AzureMapsGettingStarted Code Samples: https://aka.ms/AzureMapsSamples Videos: https://aka.ms/AzureMapsVideos Blog: https://aka.ms/AzureMapsBlog Developer Forums: https://aka.ms/AzureMapsForums Azure Maps IoT School: https://aka.ms/AzureMapsIoTSchool Case Studies: https://aka.ms/AzureMapsCaseStudies9 Tutorials from the Azure Maps Team
In order to showcase the possibilities with the Azure Maps API's, the Azure Maps team has put together a few walkthrough tutorials. They are great if you want to kick the tires and get a feel of whats possible with Azure Maps.. Try them out : Setting Up a Geofence Implement IoT spatial analytics using Azure Maps Electric vehicle routing using Azure Notebooks (Python) Search nearby points of interest using Azure Maps Route to a point of interest using Azure Maps Find routes for different modes of travel using Azure Maps Create a store locator by using Azure Maps Retail Catchment Area Analysis Analyze Weather Data using Azure NotebooksCatchment Area Analysis for a Café in Seattle using Azure Maps
Jump directly to the code, if you'd rather: http://bit.ly/2lAC2jS Catchment is defined as the sphere of influence from which retailers draw their customers. Azure Maps can be used by Retailers to better understand a location and analyze business drivers and disruptors from a spatial perspective. By building isochrones around the store location retailers can search within the Isochrone to determine the demographic mix, parking spaces, competitors and other information that could potentially help drive traffic to, or from, the business. I have been experimenting with Jupyter Notebooks as a great way to create and share my Azure Maps experiments with live code, visualizations and narrative text. Jupyter Notebooks are also an excellent way to do ad-hoc analysis using its interactive code-base environment. The Route Range (Isochrone) API helps calculate a set of locations that can be reached from the origin point based on fuel, energy, or time budget that is specified. A polygon boundary (or Isochrone) is returned in a counterclockwise orientation as well as the precise polygon center which was the result of the origin point. This API is excellent for determining the Catchment Area for a retail location. In my code experiment, I used a 10-minute walking zone around a Starbucks store in downtown Seattle. Once I built the Isochrone around the store, I could use the Search Geometry endpoint to try and find business drivers and disruptors for that Starbucks store. For instance, fastfood chains are now a big disruptor to coffee chains like Starbucks and could be considered business disruptors. I set the search term in my code to "fastfood" and it found 11 fastfood establishments within a 10 minute walk of the Starbucks location: 1 . Gyros Place 2 . Peach Labs 3 . McDonald's 4 . Hot Dog Joes 5 . Taqueria 6 . Gyro Stop 7 . Jack in the Box 8 . McDonald's 9 . Buffalo Wild Wings 10 . Street Hot Dog Stand 11 . Monster Dogs On the other hand, an abundance of parking locations is a business driver. When I change the query to look for Parking within a 10 minute zone of the Starbucks, I do get plenty of options (it shows over 50 parking lots within the isochrone). Try experimenting by changing the query to different business drivers and disruptors. Establishing a score for the business drivers and disruptors will enable you to establish a profitability score for your location. You can download the code from my github repo. You can experiment with the downloaded code using Azure Notebooks. I will be posting a detailed blog shortly but the embedded narrative in the Jupyter Notebook, is, I hope, pretty detailed.Visualizing locations and paths on a map with Azure Maps
I've been working on tracking animals (fake ones, not real ones!) for an example project using a GPS device connected to AzureIoT Hub. I wanted to plot this data on an interactive map control shown on a web page, showing individual sightings as pins andcontinuous tracking as paths. I did this using Azure Maps, andwrote a blog post on how to show pins and paths: dev.to/azure/visualizing-locations-and-paths-on-a-map-with-azure-maps-906 Follow me on Twitter for updates when I publish more Azure Maps and IoT content.Checking Geofences with Azure Maps
I've been playing with Geofences recently. I have an IoT device with a GPS sensor and wanted to track when this device leaves a geofence - a defined region on a map. In my case I'm building a sample for a wildlife tracker, so I want to be notified if the animal enters an area of population. My GPS data feeds into Azure IoT Hub, and a Function is triggered off each event to check the GPS coordinates against a geofence. Read the blog post here: dev.to/azure/are-you-where-you-should-be-checking-geofences-using-azure-maps-2icd Follow me on Twitter for updates when I publish more Azure Maps and IoT content.Address Collection with Azure Maps Search
Whether you have a list of addresses or need to collect addresses from customers, the challenge exists that those addresses map to a real location! As you or your company are taking valuable time to collect and likely paying for space to store this information it is important that it be free of misspelling and contain only verified information. With Azure Maps you can create your own address generation experience that covers the world (Geocoding coverage in Microsoft Azure Maps Search service | Microsoft Docs) and tailor it to meet your needs. Here are some ideas how you might power your address collection solution by leveraging Azure Maps Search API. Use Predictive Mode to provide suggested addresses If you are building an experience that collects address information through a web site or form, you can allow only suggested addresses to be entered by having the client enter their address details and only select from a drop down of addresses choices. The Azure Maps Search API has a parameter,typeaheadthat when set totrue will treat the query value as a partial input and sets the API into a predictive mode, assuming that this is incomplete data. You can try our sample solution yourself at Fill Address Form with Autosuggest - Azure Maps Web SDK Samples (azuremapscodesamples.azurewebsites.net) and pull the code from GitHub to modify for use in your solution. Using the samples steps in the Best practices for Azure Maps Search Service | Microsoft Docs you will see the following drop-down experience in the sample: And each of these choices will have a corresponding address in the Search response. Let’s choose the first one, Charlotte. It has the following address that includes some deeper detail: "address": { "streetName": "Microsoft Way", "municipalitySubdivision": "Charlotte", "municipality": "Charlotte", "countrySecondarySubdivision": "Mecklenburg", "countryTertiarySubdivision": "Township 1 Charlotte", "countrySubdivision": "NC", "countrySubdivisionName": "North Carolina", "postalCode": "28273", "extendedPostalCode": "282738105, 282738106, 282738108, 2827382, 282738200", "countryCode": "US", "country": "United States", "countryCodeISO3": "USA", "freeformAddress": "Microsoft Way, Charlotte, NC 28273" } Once I select that option from the drop down the form can be filled with the values from the Search call response, confident that this is a valid address as shown: Confirming visual address location with Azure Maps Search If you are building an experience to validate a physical delivery address, you can use the same method but validate the location against a map instead of entering text in a form. As in the prior sample, the client enters the details of the delivery location but now they can confirm that the correct location by seeing where a pin is placed on the map. If not, they can type more details to change the suggestion options. To try this scenario for yourself, go to Search Autosuggest and JQuery UI - Azure Maps Web SDK Samples (azurewebsites.us) Existing address match with Azure Maps Search Last but not least, if you already have a database or collection of addresses you want to check, the same Azure MapsGet Search Address APIreceives queries that contain location information, and returns results as latitude and longitude coordinates. This API can be called individually or as a batch as documented here Search - Post Search Address Batch (Azure Maps) | Microsoft Docs. By filtering the results, you can identify addresses that failed to resolve and reach out to that client for an update to their address, ensuring that invalid addresses are identified and repaired. In summary, with Azure Maps, there is a path to only keeping valuable and verified addresses in your solution. Please find these interactive samples and many more to help you with your Azure Maps solution at Azure Maps Web SDK Samples (azuremapscodesamples.azurewebsites.net).Azure Maps at Smart City Expo & World Congress
According to the UN, we will see the worlds urban populations grow from todays 55% to 68% by 2050. With almost a billion people on the path to be urban dwellers, most cities are still unfriendly to people with disabilities. As more people flock to cities, making our cities smarter and more inclusive will become increasingly important. The concept of smart cities is all about developing strategies that leverage data and technology to enhance urban life: The Internet of things plays a central role in collecting sensor data and then using the insights gained from that data to manage assets, resources and services efficiently. As city planners tackle the complex challenges of increasing urbanization, managing scarce resources, climate change and creating safer more accessible cities, Azure Maps, set of Geospatial APIs, becomes a critical tool for city planners. In order to connect with cities on their journeys for digital transformation, the Azure Maps team will be at Smart City Expo World Congress, the industry-leading event for urbanization, showcasing technologies and partners enabling the digital transformation of smart cities. Visit our booth at Gran Via, Hall P2, Stand 223 and chat with us on how Geospatial Analytics & Location Intelligence can help Smart Cities. I will be showcasing interesting solutions from partners as well as showcasing some of the demos that the team has put together. We will have Azure Maps demos from : 1. Perceptual Informatics 2. Aira 3. Moovit 4. Unacast I have been working with an early developer preview of the Azure Maps integration with Power BI. This will be available for Public Preview in early CY20. I will be showcasing a few scenarios for Smart CIties including Transit & Mobility and several other scenarios combining Weather, traffic and Open Data from Cities. Swing by the Microsoft Azure Maps station at the Microsoft Booth for some interesting ideas, conversation & demos to help inspire you with Smart City solutions.Azure Maps: Best of Breed Content Partnerships
Continuing on the path to provide customers with the best of breed content in a seamless manner, the Azure Maps team is pleased to announce, in partnership with Accuweather, the preview of a new set of Weather Services for Azure customers to integrate into their applications. With the inclusion of Weather Services as part of the Azure Maps API, customers can seamlessly integrate current & forecast weather into their geospatial analytics as well as weather along a route. Azure Maps users can now seamlessly access TomTom, Moovit and Accuweather content seamlessly using the Azure Maps API without the overhead of data integration and licensing costs. The Azure Maps partnership with TomTom enables customers to access the freshest maps and traffic information.Moovit is an early pioneer of Mobility as a Service (MaaS) and the developer of a free public transit app with more than 300 million registered users in over 2,600 cities in 85 countries. Moovit amasses four billion anonymous data points a day to add to the world’s largest repository of transit & ride share data.Integrating Moovit’s transit data into Azure Maps help developers build richer apps using public transit& ride share data. The combination of the data sources like real time traffic, real time transit and ride share data as well as real time & forecast weather with the geospatial and location intelligence capabilities of Azure Maps enables customers to solve business challenges that take into account weather, traffic and transit options. We would love to hear interesting stories and examples of how you have used the various content sources with Azure Maps.
