Dimensional Data

Did you know how easy it is with RAD Studio Delphi to add powerful, enterprise-grade real-time streaming to and from IoT devices? We’re going to show you how to get your apps to talk to IoT devices securely and in a robust fashion in just a few easy steps. IoT and Delphi – linking the “internet of things” IoT is very popular these days and the number of connected devices are growing at unprecedented rate. We can find “things” connected to the internet and used for all sorts of applications in our homes, offices, industry and commerce. In fact, they’re so ubiquitous we sometimes don’t even notice them and the form factor they take can be non-obvious too, taking such ephemera as ‘smart’ dog collars, luggage tags, or even automated egg monitors in chicken farms. These physical devices usually have integrated software to allow them to communicate with each other and of course to provide useful information to humans. Many are designed to do that with little to no human intervention. I took a look at a small internet search for “connected devices” to see what would come up: Google Home Voice Controller Amazon Echo Plus Voice Controller Amazon Dash Button August Doorbell Cam August Smart Lock Kuri Mobile Robot Belkin WeMo Smart Light Switch Footbot Air Quality Monitor Flow by Plume Labs Air Pollution Monitor Nest Smoke Alarm IoT devices have a common theme IoT devices have two things in common: Capability to connect to the internet. After all, it’s the “I” in “IoT”. Having some inbuilt technology to provide their functionality such as sensors, functional software and the connectivity. The market for IoT devices is increasing surprisingly. We have now reached the stage where there are more IoT devices than humans. What is IPWorks IoT? IPWorks IoT is a light-weight library which you can use in your Delphi and C++ builder applications to easily integrate IoT communication protocols. It supports all of the common protocols. IPWorks has a long history and has been a very reliable framework for over 25 years now. These IoT components are based on those IPWorks framework so you don’t have to worry about their security and reliability. Another great feature is the components do not depend on any external libraries or similar dependencies. Also the components are thread safe which is an added bonus when dealing with multiple devices with potentially simultaneous flows of real-time data. The icing on the cake is that IPWorks has a great active online knowledge base. Where can I get IoT components for Delphi? You can get IPWorkis IoT from Getit libraries: https://getitnow.embarcadero.com/trial-ipworks-iot-2020-delphi-edition/ How do I implement MQTT with IPWorks IoT? MQTT stands for MQ Telemetry Transport. MQTT is the OASIS standard for IoT messaging. MQTT is basically designed for low resources scenarios such as microcontrollers. MQTT use less bandwidth than other protocols such as HTTP. Message headers are smaller and the overhead in sending/receiving them is correspondingly lightweight too. MQTT is bidirectional. Also it allows message broadcasting. Messaging is very reliable. There are three levels of QoS. At most once (0) At least once (1) Exactly once (2) MQTT is very useful in unreliable networks. With MQTT persistent sessions, you can reduce the bandwidth and response time. Also you can setup TLS and transfer data securely. IPWorks […]

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Angular is an extremely popular and powerful web application design framework. It’s a development platform for creating highly efficient and sophisticated single-page apps. Angular is built on TypeScript which is a strongly-typed super-set of JavaScript. The TypeScript framework shares a parentage with Delphi since the project is headed by Microsoft’s Anders Hejlsberg who we all know better as the original creator of Delphi. Anders is still very active in the TypeScript project. TypeScript was designed to overcome some of the shortcomings of JavaScript and in particular to try and use the lessons learned with Delphi’s superb type system to help prevent very common and subtle errors which crop up frequently in JavaScript when developers accidentally misuse an object. What sort of features does Angular include? It’s a component-based framework for building scalable web applications. TypeScript has a collection of well-integrated libraries that cover a wide variety of features, including routing, forms management, client-server communication, and more TypeScript has a suite of developer tools to help you develop, build, test, and update your code With Angular, you’re taking advantage of a platform that can scale from single-developer projects to enterprise-level applications. Angular is designed to make updating as easy as possible, so you can take advantage of the latest developments with a minimum of effort. Best of all, the Angular ecosystem consists of a diverse group of over 1.7 million developers, library authors, and content creators. What can we do with Angular and Delphi? Of course many things we can do using Delphi, one of them is by serving Angular application using it, so let’s create simple web application using Angular. Here are the steps: Running Angular with Delphi Run application and point your browser to http://localhost:8080/index.html , you should see something like the image below: Easy isn’t it ? Please check updated code here https://github.com/checkdigits/horse-API-Demo

No matter how big, successful or important we may, or may not, become in our lives we are all just tiny ants in a vast Cosmos. It’s humbling and useful to remember when you’re having a bad Monday or a terrific Tuesday that we’re each just one of 7.5 billion people hurtling around the Sun. That circuit of the Sun, of course, has fascinated humankind for thousands of years, provoking ancient British Iron Age people to build Stonehenge and Egyptian pharaohs to worship it as the deity Ra. In the English language we even have a day of the week named after it. Our whole wide world in the palm of your hand So with this solar preoccupation it’s perhaps no surprise that there is a striking mobile app from Belgian developer MICRI Consult based in Oostende which helps us to visualize the Earth, its position in space relative to the Sun and how the shadow of night glides across our globe’s surface. It’s at once both a terrific teaching aid for children and adults alike, a useful reference for the physics and astronomical data involved and a beguilingly addictive game too. That’s a pretty clever trick to pull off in a mobile app! How is this native Android app produced? Written in the richly powerful cross-platform FireMonkey FMX framework using RAD Studio Delphi, the Earth Positions app really helps us picture anything we could ever want or need to know about the relationship between the Sun and our blue planet home. Learning is made more fun through clever use of educational games and smooth, rich video animations to engage little learners and the bigger ones too! Great stuff by MICRI Consult What does the Earth Positions app do? The app has three main feature animations The Geographical game, where you have to guess a location on a 3D-earth, which rotates and tumbles to display that location in the middle. This game contains 4 levels (beginner, skillful, advanced and expert), 5 continents (Africa, America, Asia, Europe and Oceania) and 5 groups (capitals, large cities, airports, towns and other). Users can get up to 3 hints and depending on the level, you may have to choose between 3, 6, 9 or 12 possibilities. It contains more than 3000 locations, of which 243 capitals and 108 large cities. Day and night, showing the shape of the night over the earth for any given date and time. It also shows the time at different earth positions and the city lights of the capitals and large cities at night. At the start, the animation shows the current day, but you can select any date to observe how shape of the night changes during the seasons, e.g. March 21, June 21, September 21 and December 21. The earth orbiting around the sun, showing the actual date for each position, the seasons and the special orbit positions of the earth. You can also select any date to indicate it on the orbit. Google Play Earth Positions Screenshot Gallery Do you want to produce a beautiful app with high-performance, native power – RAD Studio can help you do it. Why not download a trial today?

Analyzing time series can be a heavy burden for your apps. The calculations involved can vary from reasonably simple to mind-numbingly complex and doing it the wrong way can bring even a desktop machine to its knees. We’re going to show you five different ways to perform high-performance analysis on a time series to truly add enterprise-grade power to your apps in a scalable, responsive way. What is Time Series Analysis? Time Series is an ordered sequence of data points which spread over a period of time. Thus it is a sequence of discrete-time data. The Time Series Data is monitored over constant temporal intervals. This data can be in any measurable and quantifiable parameter related to the field of business, science, finance, etc (for example: Heights of ocean tides, counts of sunspots, the daily closing value of the Dow Jones Industrial Average, etc.). Time Series Analysis refers to identification of the common patterns displayed by the data over a period of time. For these tasks, experts employ specific methods to study the data’s characteristics and extract meaningful statistics that eventually aid in forecasting. Time Series Analysis is beneficial and commonly used for Economic Forecasting, Yield Projection, Inventory Studies, Census Analysis, Sales Forecasting, Stock Market Analysis, Budgetary Analysis, etc. Why use Python for Time Series Analysis? Python is a general-purpose interpreted programming language (unlike R or Matlab). Easy to learn and use primarily because it focuses on readability. It is a popular language in general, consistently appearing in the top 10 programming languages in surveys on StackOverflow (for example, the 2015 survey results). Python is a dynamic language and very suited to interactive development and quick prototyping with the power to support the development of large applications. Python is also widely used for Machine Learning and Data Science because of the excellent library support (in this post, you will learn how to implement Machine Learning for Time Series tasks). It means that you can perform your research and development (figuring out what models to use) in the same programming language that you use in productions, greatly simplifying the transition from development to production. Read more here, for Why use Python for Scientific Computing: Delphi adds Powerful GUI Features and Functionalities to Python In this tutorial, we’ll build Windows Apps with extensive Time Series Analysis capabilities by integrating Python’s Computer Vision libraries with Embarcadero’s Delphi, using Python4Delphi (P4D). P4D empowers Python users with Delphi’s award-winning VCL functionalities for Windows which enables us to build native Windows apps 5x faster. This integration enables us to create a modern GUI with Windows 10 looks and responsive controls for our Python Computer Vision applications. Python4Delphi also comes with an extensive range of demos, use cases, and tutorials. We’re going to cover the following… How to use PyDSE, statsmodels, sktime, Nitime, and tslearn Python libraries to perform Time Series Analysis All of them would be integrated with Python4Delphi to create Windows Apps with Time Series Analysis capabilities. What do I need to perform time series analysis? Before we begin to work, download and install the latest Python for your platform. Follow the Python4Delphi installation instructions mentioned here. Alternatively, you can check out the easy instructions found in the Getting Started With Python4Delphi video by Jim McKeeth. Time to get Started! First, open and run our […]

REST AI APIs are really easy to use with RAD Studio Look, we have been spoiling you a little too much on this site. We keep showing you how few lines of code it is to call APIs on public REST servers. We showed you comparison tests which proved that the skilled Delphi developers in the test were nearly 7 times faster than some competing technologies. We’ve published a total smorgasbord of articles about how totally easy it is to use RAD Studio Delphi to perform artificial intelligence, machine learning and deep learning along with some nifty demonstrations integrating image processing in your apps. We really mean it when we say RAD Studio Delphi makes difficult tasks easier. We know though, you might not believe us. So here’s how to include artificial intelligence into your apps by using a REST API the really difficult way. What can be done with DenseCap Artificial Intelligence? DenseCap detects objects in an image. It creates a JSON object containing coordinates of detected objects and readable captions for them. In the left side of title picture, you see the image processed. The middle part shows starting lines of the JSON object text representation. The DenseCap page contains the product description. The mathematical background is described in this PDF document. For demo purposes, we chose the simplest – draw the found objects on initial image. You see it in the right part of title picture. An important practical usage – process a large image library and store extracted data in DB. This DB can be used to search images or fragments by caption texts. How do I use the DenseCap AI API in my applications? A DenseCap wrapper is available as a C# Nuget package. Available also C# source and JavaScript source in GitHub, but they are a bit obsolete. The DenseCap C# Nuget package does not expose COM interface. Therefore, we should create a wrapper DLL in Visual Studio. C# usage for two tasks, image file and image UR, proposed by DenseCap developers, is following: Our aim is a CLR C++ exporting two functions: __declspec(dllexport) BSTR Densecap_ProcessFile(BSTR key, BSTR filename); __declspec(dllexport) BSTR Densecap_ProcessUrl(BSTR key, BSTR url); __declspec(dllexport) BSTR Densecap_ProcessFile(BSTR key, BSTR filename); __declspec(dllexport) BSTR Densecap_ProcessUrl(BSTR key, BSTR url); These functions return strings – JSON object textual representations. For further processing in Delphi, these strings can be converted in JSON again. Unfortunately, currently Visual Studio CLR C++ does not support Nuget import. So, two wrappers required, C# importing Nuget and CLR C++ exporting desired functions. A complete solution available at the following link: https://github.com/checkdigits/Embarcadero_DenseCap2 All binaries required for Delphi are placed in the “Release: folder.. To work with Delphi, you do not need Visual Studio, simply download files from this folder. And now, you can skip chapters about Visual Studio, and go directly to the Delphi part. C# wrapper – project DeepAICsWrapper Right click on the project, select “Manage Nuget Packages”: Type DeepAI. Press Install. Selected package appears together with packages it depends on. Press OK. Create two static functions, for file and URL. Build the project. C++ CLR wrapper – project DeepAIClrWrapper Add a new C++ project – CLR Class Library. Right click References, add a reference to the recently created DeepAICsWrapper Required functions are in DeepAIClrWrapper.h, leaving cpp empty. Build the project. Using the […]