Monat: Januar 2019

AI & IoT Insider Labs: Helping transform smallholder farming

This blog post was authored by Peter Cooper, Senior Product Manager, Microsoft IoT.

From smart factories and smart cities to virtual personal assistants and self-driving cars, artificial intelligence (AI) and the Internet of Things (IoT) are transforming how people around the world live, work, and play.

But fundamentally changing the ways people, devices, and data interact is not simple or easy work. Microsoft’s AI & IoT Insider Labs was created to help all types of organizations accelerate their digital transformation. Member organizations around the world get access to support both technology development and product commercialization, for everything from hardware design to manufacturing to building applications and turning data into insights using machine learning.

Here’s how AI & IoT Insider Labs is helping one partner, SunCulture, leverage new technology to provide solar-powered water pumping and irrigation systems for smallholder farmers in Kenya.

Affordable irrigation for all

Kenyan smallholdings face some of the most challenging growing conditions in the world. 97 percent rely on natural rainfall to support their crops and livestock—and the families that depend on them. But just 17 percent of the country’s farmland is suitable for rainfed agriculture. Electricity is unavailable in most places and diesel power is often financially out of reach, so farmers spend hours every day pumping and transporting water. This limits them to low-value crops like maize and small yields, all because they lack the resources to irrigate their crops. Additionally, irrigation technologies have an important role to play in reducing the impact agriculture has on the earth’s freshwater resources, especially in Africa.

SunCulture, a 2017 Airband Grant Fund winner, believed sustainable technology could make irrigation affordable enough that even the poorest farmers could use it without further aggravating water shortages. The company set out to build an IoT platform to support a pay-as-you-grow payment model that would make solar-powered precision irrigation financially accessible for smallholders across Kenya.

How SunCulture’s solution works

SunCulture’s RainMaker2 pump combines the energy efficiency of solar power with the effectiveness of precision irrigation, making it cheaper and easier for farmers to grow high-quality fruits and vegetables. Using the energy of the sun, the SunCulture system pulls water from any source—lake, stream, well, etc.—and pumps it directly to the farm with sprinklers and drip irrigation.

This cutting-edge solution combines ClimateSmart™ solar and lithium-ion energy storage technology with cloud-based remote monitoring and optimization software developed with support from AI & IoT Insider Labs. It’s a powerful platform that makes it simple and cheap to deploy off-grid energy and connected solutions.

Farmers get the information they need to make good irrigation decisions at scale, without the costs involved in sending agronomy experts into the field. How? SunCulture processes a steady flow of sensor data, like soil moisture, pump efficiency, solar battery storage, and other factors, that is analyzed within Microsoft Azure’s cloud environment. This sensor data is combined with data from SunCulture’s network of 2,000 hyperlocal weather stations to leverage Azure machine learning tools and provide simple, real-time, precision irrigation recommendations directly to the farmer via text messaging (SMS).
 
The platform also enables real-time locking and unlocking of devices that makes the pay-as-you-grow model feasible. The platform is smart enough to shut off pumps automatically when power levels are getting low on a cloudy day, or when optimal irrigation thresholds are reached.

How farmers are benefiting from SunCulture

SunCulture's pay-as-you-grow revenue model allows farmers to make small, monthly payments until they own their precision sensor-based irrigation system outright, empowering even the region’s poorest smallholder farmers to take control of their environment.

On average, SunCulture customers enjoy a 300 percent increase in crop yields and a 10x increase in annual income. Farmers with livestock double their milk yield, earning an extra $3.50/day in income from milk alone. The 17 hours per week they used to spend moving water manually is now directed to better tending their crops and livestock. At a price point of $1.25/day for the RainMaker2 with ClimateSmart™, a farmer’s investment is recouped quickly, and profit starts flowing from increased agricultural productivity.

Download SunCulture’s case study to learn more.
Quelle: Azure

Analyze data in Azure Data Explorer using KQL magic for Jupyter Notebook

Exploring data is like solving a puzzle. You create queries and receive instant satisfaction when you discover insights, just like adding pieces to complete a puzzle. Imagine you have to repeat the same analysis multiple times, use libraries from an open-source community, share your steps and output with others, and save your work as an artifact. Notebooks helps you create one place to write your queries, add documentation, and save your work as output in a reusable format.

Jupyter Notebook allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. Its includes data cleaning and transformation, numerical simulation, statistical modeling, and machine learning.

We are excited to announce KQL magic commands which extends the functionality of the Python kernel in Jupyter Notebook. KQL magic allows you to write KQL queries natively and query data from Microsoft Azure Data Explorer. You can easily interchange between Python and KQL, and visualize data using rich Plot.ly library integrated with KQL render commands. KQL magic supports Azure Data Explorer, Application Insights, and Log Analytics as data sources to run queries against.

Use a single magic “%kql” to run a single line query, or use cell magic “%%kql” to run multi-line queries. In the following example we run a multi-line query and render a pie chart using the ploy.ly Python library:

If you are a Python user, you can place the result set into a pandas dataframe.

Common use cases

Data science: Data scientists use KQL magic to analyze and visualize data from Azure Data Explorer, easily interchange Python code with KQL queries to experiment, train, score machine learning models, and also save notebooks as artifacts.
Data analytics: Use KQL magic to query, analyze, and visualize data, with no Python knowledge needed. For Python users, easily query data from Azure Data Explorer and use various open-source libraries from the Python ecosystem.
Business reviews: Use KQL magic for business and product reviews. Create the notebook once and refresh with new values every time you use it.
Incident response: Use KQL magic to create operational documents, chain-up your queries for easy investigation, save the notebook for reproducibility and artifacts for remote connectivity analyzer (RCA).
Security analytics: Query data from Azure Data Explorer and use the rich Python ecosystem for security analytics to analyze and visualize your data. For example, one of the internal Microsoft security teams uses KQL magic with Juypter for standard analysis patterns to triage security alerts, they have been transforming incident response playbooks into parameterized Jupyter Notebooks to automate repetitive investigation workflows. A sample notebook is available in the Azure Data Explorer KQL magic Demo and in GitHub Repo under Threat-hunting-with-notebooks.

Getting started

Our exciting capabilities will allow you to have fun with your data analytics. You can see additional documentation and examples of KQL magic by visiting our documentation, “Analyze data using Jupyter Notebook and KQL magic.”
Quelle: Azure

Security for healthcare through vigilant agents and virtual patching

Healthcare organizations depend on data-driven decisions. To enable better decisions and better health outcomes, healthcare organizations are moving to the cloud. There, the latest advances in artificial intelligence, machine learning, and analytics can be more easily tested and implemented. For a healthcare organization, security and protection of data is a primary value, but solutions can be attacked from a variety of vectors such as malware, ransomware, and other exploits. The attack surface of an organization could be complex, email and web browsers are immediate targets of sophisticated hackers. One Microsoft Azure partner is devoted to protecting healthcare organizations despite the complexity of the attack surface. XentIT (ex-ent-it) leverages two other security services with deep capabilities and adds its own expertise to create a dashboard-driven security solution that lets healthcare organizations better monitor and protect all assets.

Problem: Slow information velocity

Anyone in a critical health condition wants their medical professionals to be up to date. Speed matters, and making a medical decision requires all sources of information to be available as soon as possible. The inability to quickly access and process patient data due to outdated infrastructure may result in a life or death situation.

Solution: Agents and virtual patching

The healthcare cloud security stack (HCSS) for Azure helps healthcare entities modernize the IT infrastructure, while maintaining focus on cloud security and compliance. The unified dashboard of HCSS provides a single pane of glass into the vulnerabilities identified by Qualys, the number and types of threats stopped by Trend Micro Deep Security, and intelligence for further investigation and remediation by security analysts and engineers. The unified stack eliminates the overhead of security automation and orchestration after migration to the cloud.

The figure below shows the architecture of a solution built on Azure with the XentIT dashboard monitoring the components, and the Qualsys service built in.

Benefits

Full implementation of Qualys Vulnerability Management, Cloud Agents, and Trend Micro™ Deep Security™.
Extensive environment configuration.
A unified dashboard view of security protection, tailored for healthcare organizations.
Optimized for Microsoft Azure to ensure flexible, scalable protection of your operating systems, applications, and data against vulnerabilities. Detect suspicious activity, stop targeted attacks, and meet compliance from within one security console.
Vulnerability Management continuously scans and identifies vulnerabilities with six sigma 99.99966 percent accuracy, protecting your Azure infrastructure. The Cloud Agent is lightweight, self-updating, and provides continuous data collection for IT security and compliance applications.

Microsoft technologies

The solution uses several Azure services.

Azure SQL Database
Data Encryption — such as SQL Server Always Encrypted
Key Vault
Load Balancer
Azure Monitor
Network Security Groups
Storage
Web Application Firewall (WAF)

“HCSS’ continuous monitoring, fast detection, and efficient remediation of vulnerabilities enables healthcare organizations to effectively secure workloads on an ongoing basis, empowering them to fully realize the benefits of Azure, accelerate the delivery of better patient care, reduce healthcare costs, and improve the experience of both patients and healthcare professionals.”

– Hector Rodriguez, Director, Worldwide Commercial Health at Microsoft

To find out more about the solution, go to XentIT in the marketplace and select “Contact me.”
Quelle: Azure