Category Archives: Apple

Adaptive mobile apps that change based on personal context

That title get your attention?  Yes, it really read “Adaptive mobile apps that change based on personal context” – with near real-time rules application, without much extra development effort.  If that sounds interesting to you, or like a product you might want to use within your own apps, then you might want to check out this site where you can get involved in the product’s development:

IBM is looking for your input on creating these types of mobile app experiences. User experiences within a single app that can be dramatically different per user based on location, past behavior, profile information, social media activity, and so much more.  With this behavior being driven by configurable rules that can be changed without redeploying an app to the app store.

How it works for your customer

Consider this scenario:

Jon and Andrea download the mobile app for S&W, a retailer known for its attention to providing great customer service. Over the next month, Jon and Andrea use the app to browse and discover content and merchandise differently.

Jon primarily navigates to sports related content for his favorite teams to find gear and clothes for travel to his favorite team’s games. Andrea scours the app for sales and fashion trends and usually ends up following her favorite designers.

Andrea and Jon go to a baseball game together. She’s never enjoyed watching it, so she opens up the S&W app to entertain herself, and her app’s navigation quickly steers her through Spring fashion articles.

Jon however, wants to replace the hat he’s worn the last three times the team lost, and since he’s in the stadium, his S&W app opens right up to the team’s gear page. The app knows he’s out of town and tells him how to get to an S&W store.

How it works for the dev team

Consider another scenario:

One of the developers on the team, George, sets up the system and application. He then gives access to Janet who is responsible for the customer experience.

Janet writes rules defining how the application could adapt and become more personalized based on inputs like , social media, geolocation, app usage, or customer information data.

Once Janet has built out her rules, she simply hits ‘Submit’ and can immediately see her clever interactions reflected in the mobile application without having to involve the development team.

Analytics let Janet know which adaptations are working best, and helps her find new opportunities to optimize the app’s user experience.

Sound interesting yet?  Check it out, and get involved in the product development at:

We’re not talking about a content management system, or translation based on locale, instead a rules-driven product that can adapt literally every aspect of your app:  customize the user interface, enable or disable different features, customized messaging and notifications, and much more, all variable based upon the user context.  This can be used to present contextually relevant information, drive adoption, provide more/less data depending on your physical context, and so much more.

It won’t be tied to a specific UI framework, won’t be tied to a specific content management system, isn’t attempting to re-create Google Now or Apple Proactive Assistance.  Rather, a set of tools and a rules engine that enable you to customize and tailor the app experience to the individual user.

Head over to to learn more and get involved!

Voice-Driven Native Mobile Apps with IBM Watson & IBM MobileFirst

Update: The IBM Watson team just announced a new native SDK for both iOS and Android that simplifies and streamlines integration with Speech To Text and Text To Speech services.  Check out more detail here: IBM Watson Speech Services Just Got A Whole Lot Easier.

Using your voice to drive interactions within your app is a powerful concept. It is the primary interaction driving Apple’s Siri, Microsoft’s Cortana, and Google’s Voice Actions. By analyzing spoken words, voice commands allow you to complete possibly complex actions with minimal interaction with the device. Or, they enable entirely different forms of interaction, for example, interacting with a remote system through the telephone.

Voice driven interactions are essentially a two part process:

  • Transcribe audible signal to text transcript
  • Perform a system action by parsing text transcript

If you think that voice-driven apps are too complicated, or out of your reach, then I have great news for you: They are not! Last week, IBM elevated several IBM Watson voice services from Beta to General Availability – that means you can use them reliably in your own systems too!

Let’s examine the two parts of the system, and see what solutions IBM has available right now for you to take advantage of…

Transcribe audible signal to text transcript

Part one of this equation is converting the audible signal into text that can be parsed and acted upon. The IBM Speech to Text service fits this bill perfectly, and can be called from any app platform that supports REST services… which means just about anything. It could be from the browser, it could be from the desktop, and it could be from a native mobile app. The Watson STT service is very easy to use, you simply post a request to the REST API containing an audio file, and the service will return to you a text transcript based upon what it is able to analyze from the audio file. With this API you don’t have to worry about any of the transcription actions on your own – no concern for accents, etc… Let Watson do the heavy lifting for you.

Perform a system action by parsing text transcript

This one is perhaps not quite as simple because it is entirely subjective, and depends upon what you/your app is trying to do. You can parse the text transcript on your own, searching for actionable keywords, or you can leverage something like the IBM Watson Q&A service, which enables natural language search queries to Watson data corpora.

Riding on the heels of the Watson language services promotion, I put together a sample application that enables a voice-driven app experience on the iPhone, powered by both the Speech To Text and Watson Question & Answer services, and have made the mobile app and Node.js middleware source code available on github.

Watson Speech QA for iOS

This native iOS app, which I’m calling “Watson Speech QA for iOS” allows you to ask Watson questions in natural, spoken language, and receive textual responses based on the Watson QA Healthcare data set.

Check out the video below to see it in action:

Bluemix Services Used

This app uses three services available through IBM Bluemix:

  1. Speech to Text – Convert spoken audio into text
  2. Question & Answer – Natural language search
  3. Advanced Mobile Access – Capture analytics and logs from mobile apps running on devices
App Architecture
IBM Watson Speech QA for iOS App Architecture

The app communicates to the Speech to Text and Question & Answer services through the Node.js middelware tier, and connects directly to the Advanced Mobile Access service to provide operational analytics (usage, devices, network utilization) and remote log collection from the client app on the mobile devices.

For the Speech To Text service, the app records audio from the local device, and sends a WAV file to the Node.js in a HTTP post request. The Node.js tier then delegates to the Speech To Text service to provide transcription capabilities. The Node.js tier then formats the respons JSON object and returns the query to the mobile app.

For the QA service, the app makes an HTTP GET request (containing the query string) to the Node.js server, which delegates to the Watson QA natural language processing service to return search results. The Node.js tier then formats the respons JSON object and returns the query to the mobile app.

The general flow between these systems is shown in the graphic below:

IBM Watson Speech QA for iOS - Logic Flow
IBM Watson Speech QA for iOS – Logic Flow


Code Explained

Mobile app and Node.js middleware source code and setup instructions are available at:

The code for this example is really in 2 main areas: The client side integration in the mobile app (Objective-C, but could also be done in Swift), and the application server/middleware implemented in Node.js.

Node.js Middleware

The server side JavaScript code uses the Watson Node.js Wrapper, which enables you to easily instantiate Watson services in just a few short lines of code

var watson = require('watson-developer-cloud');
var question_and_answer_healthcare = watson.question_and_answer(QA_CREDENTIALS);
var speechToText = watson.speech_to_text(STT_CREDENTIALS);

The credentials come from your Bluemix environment configuration, then you just create instances of whichever services that you want to consume.

I implemented two methods in the Node.js application tier. The first accepts the audio input from the mobile client as an attachment to a HTTP POST request and returns a transcript from the Speech To Text service:

// Handle the form POST containing an audio file and return transcript (from mobile)'/transcribe', function(req, res){

  //grab the audio WAV file attachment and prepare to send to Watson
  var file =;
  var readStream = fs.createReadStream(file.path);
  console.log("opened stream for " + file.path);

  var params = {
    content_type:'audio/l16; rate=16000; channels=1',

  //send the audio WAV file to the watson.recognize service
  speechToText.recognize(params, function(err, response) {

    if (err) {
      return res.status(err.code || 500).json(err);
    } else {
      //parse the results and return them to the client
      var result = {};
      if (response.results.length > 0) {
        var finalResults = response.results.filter( isFinalResult );
        if ( finalResults.length > 0 ) {
          result = finalResults[0].alternatives[0];
      return res.send( result );

Once you have the text transcript on the client, you could do whatever you want with it. You could parse it to invoke local actions, or delegate to a natural language query service

The second method does exactly this: it accepts a URL query parameter from a HTTP GET request and uses that parameter in a Watson QA natural language search:

//handle QA query and return json result (for mobile)
app.get('/ask', function(req, res){

  //get a copy of the search query text from the req.query object
  var query = req.query.query;

  if ( query != undefined ) {
    //perform a search using the QA "ask" method
    question_and_answer_healthcare.ask({ text: query}, function (err, response) {
      if (err){
        return res.status(err.code || 500).json(response);
      } else {
        //format the results and return them to the mobile client
        if (response.length > 0) {
          var answers = [];

          for (var x=0; x<response[0].question.evidencelist.length; x++) {
            var item = {};
            item.text = response[0].question.evidencelist[x].text;
            item.value = response[0].question.evidencelist[x].value;

          var result = {
          return res.send( result );
        return res.send({});
  else {
    return res.status(500).send('Bad Query');

Note: I am using the free/open Watson Healthcare data set. However the Watson QA service can handle other data sets – these require an engagement with IBM to train the Watson service to understand the desired data sets.

Native iOS – Objective C

On the mobile side we’re working with a native iOS application. My code is written in Objective C, however you could also implement this using Swift. I won’t go into complete line-by-line code here for the sake of brevity, but you can access the client side code in the ViewController.m file. In particular, this is within the postToServer and requestQA methods.

You can see the flow of the application within the image below:

App Flow: User speaks, transcript displayed, results displayed


The native mobile app first captures audio input from device’s microphone. This is then sent to the Node.js server’s /transcribe method as an attachment to a HTTP POST request (postToServer method on line 191). On the server side this delegates to the Speech To Test service as described above. Once the result is received on the client, the transcribed text is displayed in the UI and then a request is made to the QA service.

In the requestQA method, the mobile app makes a HTTP GET request to the Node.js app’s /ask method (as shown on line 257). The Node.js app delegates to the Watson QA service as shown above. Once the results are returned to the client they are displayed within a standard UITableView in the native app.

MobileFirst – Advanced Mobile Access

A few other things you may notice if you decide to peruse the native Objective-C code:

  1. Within AppDelegate.m you will see calls to IMFClient, IMFAnalytics, and OCLogger classes. These enable operational analytics and log collection within the Advanced MobileAccess service.
  2. All network requests inside of ViewController.m use the

    IMFResourceRequest class. Using the IMFResourceRequest class enables the collection of analytics for every request made within the application (through this class).

Together these allow for the collection of device logs, automatic crash reporting, and operational analytics that provide one of the strengths of the Advanced Mobile Access service, which is one of the mobile offerings on IBM Bluemix.

Source Code

Mobile app and Node.js middleware source code and setup instructions for this app are available at:

Just create an account on IBM Bluemix, and you have everything that you need to get started creating your own voice-driven apps.

Apple WWDC Recap for Mobile Devs

I’m sure you’ve already heard Apple’s big announcements from the annual Worldwide Developer Conference this week.  I was lucky enough to snag a ticket in Apple’s lottery and got to check it all out in person. There were lots of great sessions, with tons of content.  Here are the highlights as I saw them from a mobile developer’s perspective – *not* from the general consumer point of view.  For the most part, I think this year’s announcements highlighted the evolution and maturity of existing products and projects – no new amazing breakthoughs, but definitely steps in the right direction.

If you haven’t seen them already, the Keynote and the Platforms State of the Union videos cover most of the announcements, but not in complete detail. Just be warned, the Keynote is loaded with product marketing fluff, not just developer topics.  Once you get to “we’ve got one more thing…” you can turn off the Keynote – the Apple Music announcement has pretty much zero significance for developers.

So let’s get started…

Swift 2.0


There was a tremendous emphasis on the Swift language at this year’s WWDC event.  There was the announcement that Swift is going to be open sourced, plus many language enhancements, and nearly every piece of sample code that was shown was written in Swift.  It is very clear that Swift is Apple’s direction moving forward.

I think the open souring of Swift is a big deal b/c it opens up the language for use beyond just iOS and OSX applications.  Think about it… Perhaps another platform might adopt Switft to develops apps (Windows?), or let’s hypothetically say you really like Node.js on the backend b/c its the same language as your web front end (JavaScript, that is). What if you are developing native apps, and you’d like to write your back end in the same language as the front end mobile client, or what if you want an ECMAScript inspired language that is more structured than Node, with real Object Oriented or functional programming constructs (and what if you want something that is really multi-threaded)?  Swift is your answer. I’m willing to bet that we will see server-side Swift not long after it is open sourced.  Let’s just hope that Swift is opened in the truest sense – you know, actually accepting input and contributions from external parties.

The Swift language itself has also evolved quite significantly.  Better error handling, protocol extensions, and improved performance are a great start.  Heck, if I understood one of the speakers correctly, it’s now even faster than Objective C at runtime in some cases.

Want to learn more about Swift?  Check out these session videos from WWDC (requires Safari):

  1. What’s new in Swift
  2. Protocol Oriented Programming in Swift
  3. Optimizing Swift Performance
  4. Swift in Practice
  5. Improve Your Existing Apps with Swift
  6. Swift and Objective-C Interoperability

OS Improvements

New versions of both OS X and iOS were announced and released to  developers… OS X El Capitan and iOS 9 respectively.  Both seem to be incremental updates of the previous OSes. New apps, new features, etc… for the end users.  Not necessarily significant changes for developers.  If you’re a graphics programmer, Metal will be a big deal for you (low level graphics/gpu API), but if you’re not a graphics guru, you probably won’t even know its there.

iPad Multitasking


The new iOS 9 multitasking/side-by-side mode for iPad is going to be a great addition which brings the iPad even closer to being a full laptop replacement.  Having the ability to have multiple apps open next to each other will improve the iPad’s “get $h1t done” ability.  You’ll have to ensure that you’ve authored your apps to leverage adaptive layouts, but that’s pretty much all that you need to do to take advantage of iPad Multitasking.

These videos will get you going in the right direction for iOS multitasking and adaptive layouts:

  1. Getting Started with Multitasking on iPad in iOS 9
  2. Multitasking Essentials for Media-Based Apps on iPad in iOS 9
  3. Mysteries of Auto Layout, Part 1
  4. Mysteries of Auto Layout, Part 2
App Thinning

ios app thinning

The new “App Thinning” features in Xcode 7/iOS 9 are also a great addition.  Currently if you build an iOS app it gets bundled with lots of resources that may never be used depending on the type of device.  App thinning introduces three concepts that help minimize the footprint and increase the quality of your installed apps: App Slicing, On Demand Resources, and Bitcode. According to the presenters, these can decrease the download/installed size of your apps quite significantly.

If you haven’t seen the App Thinning in Xcode session, you should definitely check it out.

App Slicing is a new feature that creates variants of your app executable depending on the device that you are downloading the app to. So, if your app doesn’t use @3x graphics, or doesn’t use the arm7s architecture on a particular device, then they won’t be downloaded.  Likewise, if your device does leverage those assets, then the other smaller scale assets and non-used binaries won’t be downloaded.

App Slicing from iOS Docs

On Demand Resources give you the ability to download specific sets of resources from the app store as they are needed.  They are still hosted by the app store, but not part of the initial download. Let’s say you are building a platform game.  Initially the shell/navigation assets will be downloaded.  While the app is running you’ll be able to download assets for level 1, level 2, level 3, etc… incrementally as they are needed.  The system can also clean up ODR resources to conserve space using a least-recently-used cleanup routine.

On-Demand Resources from Apple Docs

Bitcode, according to the docs:

Bitcode is an intermediate representation of a compiled program. Apps you upload to iTunes Connect that contain bitcode will be compiled and linked on the App Store. Including bitcode will allow Apple to re-optimize your app binary in the future without the need to submit a new version of your app to the store.

Bitcode enables the app store to re-compile your code to take advantage of new LLVM optimizations without you even having to recompile and upload a new application binary.

UI Testing

The new UI testing features in Xcode 7 look pretty awesome as far as automated UI testing goes.  It enables you to record/playback steps and generated UI unit tests all from within Xcode.  What’s even better, it enables you to set breakpoints within your tests, so you can debug why your tests might be failing, or you can set breakpoints inside of your app, and the automated testing stops at the breakpoints and allows you to step through code while inside the automated unit test.  Definitely do not miss the session on UI Testing in Xcode 7 if you have any (even remote) interest in automated UI testing, it looks pretty darn useful.

Improved Search and Deep Linking

Improved search functionality was also announced for both iOS and OS X.  This improves the search functionality, and also enables your apps to index their content, so using the device search enables you to search for information hosted *inside* of the app.  To complement the enhanced search, there are also features that better facilitate deep linking into your app.  This enables apps to be launched directly into the appropriate content/context with greater ease.  I need to look into this more, but it sounded interesting…

Check out these resources for additional detail:

  1. Introducing Search APIs
  2. Seamless Linking To Your App


watchOS 2

Last, but by certainly no means least, the announcement of watchOS 2 looks like a massive leap forward for developing for the Apple Watch.


WatchOS 2 brings us the ability to execute code natively on the Apple Watch, not just in the WatchKit extension running on your iPhone, brings us the ability to implement custom watch complications, access to network connectivity if your phone is not connected, support for multimedia, and direct access to hardware sensors.  If you’re wondering what “watch complications” are, they are the widgets on the watch face that enable you to display customized information.

WatchOS Complications

You should definitely check out the videos on developing for the Apple Watch if you have any interest in watchOS:

  1. Building Watch Apps
  2. Introducing WatchKit for watchOS 2
  3. Layout & Animation Techniques for WatchKit
  4. WatchKit in-Depth, Part 1
  5. WatchKit in-Depth, Part 2
  6. Introducing Watch Connectivity
  7. Designing for AppleWatch

Also, don’t forget the watchOS docs, which are chock full of resources and a watchOS 2 transition guide.

There are also new APIs, enhanced features in CloudKit, MapKit, HomeKit, Core Motion, Core Location, updates to Apple Pay, security updates, networking updates, and lots more.  Be sure to check out the complete list of WWDC videos for more.

There was so much to absorb, I’m sure I missed something, so feel free to point anything out that I’ve overlooked!

Serving Data to the Apple Watch with IBM MobileFirst

This is the third entry in my series on powering Apple Watch apps using IBM MobileFirst.  In the first post I covered setting up the project, remote logging, and analytics. In the second post I covered bidirectional communication between the WatchKit extension and host app (not really MobileFirst, but still applicable).  In this post we’ll examine how to consume data from the MobileFirst Foundation Server inside of an Apple Watch app.

If you’re already familiar with consuming data using MobileFirst Adapters, then guess what… it is *exactly* the same as consuming an Adapter in a native iOS project. Since the logic for a WatchKit app is executed in the WatchKit extension, which is actually an executable that runs on the phone, there is no difference between between the two.

If you aren’t familiar with Adapters, they are server-side code that is used to transfer and retrieve information from back-end systems to client applications and cloud services.  You can write them in either Java or JavaScript, they can be consumed in any MobileFirst app, and they offer security, data transformation, and reporting metrics out of the box.

In the video below I walk through the process of recreating the Apple Watch Stocks app using data delivered from a MobileFirst Platform Foundation server instance. The data is simulated, so don’t use it for any investments. :)

The basic process was this: build out the Apple Watch apps user interface in Xcode/Interface Builder, build the adapters to expose the data, then start consuming the data within the WatchKit extension to deliver it to the watch app interface.

Full source code for this project is available at:

The User Interface

So, lets first look at the app interface.  I have two views that were built in Interface Builder.  One is a table that displays rows of data, one is a details screen which has lots of labels used to display data.


In the main interface I have a “loading…” label (that is hidden once the data is loaded) and a table that is used to display data.  For each row in the table there are 3 labels to display specific data fields. These were connected to IBOutlet references in the view controller class. All of these are straightforward WatchKit development practices.  Be sure to check out the WKInterfaceTable class reference for more detail on working with WatchKit tables.

Xcode-Interface Builder for Table View
Xcode-Interface Builder for Table View

For displaying the details screen, I also used very similar pattern.  I added labels for displaying data, and linked them to IBOutlet references in my view controller so I can change their values once the data is loaded.

Xcode-InterfaceBuilder Detail View
Xcode-InterfaceBuilder Detail View

Serving Data

Loading data into a WatchKit extension is identical to making a request to the MobileFirst server adapter from a native iOS app.  I did use my helper class so I can use code blocks instead of the delegate patter, but the implementation is exactly the same.

So, here’s how we can create an adapter using the MobileFirst Command Line Interface.  Use the “mfp add adapter” command and follow the prompts:

$ mfp add adapter
[?] What do you want to name your MobileFirst Adapter? StocksAdapter
[?] What type of adapter would you like?
 Cast Iron
 SAP Netweaver Gateway
 [?] Create procedures for offline JSONStore? No
 A new sql Adapter was added at /Users/andrewtrice/Documents/dev/MobileFirst-Stocks/server/MFStocks/adapters/StocksAdapter

Adapters can be used to easily connect back end systems to mobile clients.  You can quickly and easily expose data from a relational database, or even consume data from http endpoints and easily serialize it into a more compact mobile-friendly format.  You should definitely read more about MobileFirst adapters through the platform documentation for more detail.

What’s also great about the MobileFirst platform is that you get operational analytics for all adapters out of the box, with no additional configuration.  You can see the number of requests, data payload sizes, response times, devices/platforms used to consumes, and much more.  Plus, you can also remotely access client log messages from the mobile devices.  Take a look at the screenshots below for just a sample (these are from my dev instance on my laptop):

All of the data I am displaying is simulated.  I’m not actively pulling from a relational database or live service. However, you could use a very similar method to connect to a live data repository.

I exposed two pretty basic procedures on the MobileFirst server: getList – which returns a stripped down list of data, and getDetail – which returns complete data for a stock symbol:

function getList() {


  var items = [];
  var trimmedProperties = ["symbol","price","change"];

  for (var i=0; i<data.length; i++) {
    var item = {};
    for (var j in trimmedProperties) {
      var prop = trimmedProperties[j];
      item[prop] = data[i][prop];

  return {

function getDetail(symbol) {

  for (var i=0; i<data.length; i++) {
    if (data[i].symbol == symbol) {
      return data[i];
  return null;

Once these are deployed to the server using the CLI “mfp bd” command, you can invoke the adapter procedures from a client application, regardless of whether it is native iOS, native Android, or hybrid application.

Consuming the Data

OK, now we’re back to the native iOS project.  In either Objective-C or Swift you can invoke an adapter directly using the WLResourceRequest or invokeProcedure mechanisms.  In my sample I used a helper class to wrap invokeProcedure to support code blocks, so I can define the response/failure handlers directly inline in my code.  So, in my code, I invoke the adapters like so:

-(void) getList:(void (^)(NSArray*))callback{

  WLProcedureInvocationData *invocationData =
    [[WLProcedureInvocationData alloc]

  [WLClientHelper invokeProcedure:invocationData successCallback:^(WLResponse *successResponse) {

    NSArray *responseData = [[successResponse responseJSON] objectForKey:@"stocks"];
    //do something with the response data

  } errorCallback:^(WLFailResponse *errorResponse) {

    //you should do better error handling than this

Once you have the data within the WatchKit extension, we can use it to update the user interface.

For the data table implementation, you simply need to set the number of rows, and then loop over the data to set values for each row based on the WKInterfaceTable specification.

[self.dataTable setNumberOfRows:[self.stocks count] withRowType:@"stockTableRow"];

for (NSInteger i = 0; i < self.dataTable.numberOfRows; i++) {

  StockTableRow* row = [self.dataTable rowControllerAtIndex:i];
  NSDictionary* item = [self.stocks objectAtIndex:i];

  [row.stockLabel setText:[item valueForKey:@"symbol"]];

  NSNumber *price = [item valueForKey:@"price"];
  NSNumber *change = [item valueForKey:@"change"];
  [row.priceLabel setText:[NSString stringWithFormat:@"%-.2f", [price floatValue]]];
  [row.changeLabel setText:[NSString stringWithFormat:@"%-.2f", [change floatValue]]];

  if ([change floatValue] > 0.0) {
    [row.changeLabel setTextColor: [UIColor greenColor]];
    [row.containerGroup setBackgroundColor:[UIColor colorWithRed:0 green:0.2 blue:0 alpha:1]];
  } else if ([change floatValue] < 0.0) {
    [row.changeLabel setTextColor: [UIColor redColor]];
    [row.containerGroup setBackgroundColor:[UIColor colorWithRed:0.2 green:0 blue:0 alpha:1]];
  else {
    [row.changeLabel setTextColor: [UIColor whiteColor]];
    [row.containerGroup setBackgroundColor:[UIColor colorWithRed:0.15 green:0.15 blue:0.15 alpha:1]];

For the detail screen we’re also doing things even more straightforward.  When the screen is initialized, we request detail data from the server.  Once we receive that data, we’re simply assigning label values based upon the data that was returned.

[self.nameLabel setText:[stockData objectForKey:@"name"]];

NSNumber *change = [stockData objectForKey:@"change"];
NSNumber *price = [stockData objectForKey:@"price"];
NSNumber *high = [stockData objectForKey:@"high"];
NSNumber *low = [stockData objectForKey:@"low"];
NSNumber *high52 = [stockData objectForKey:@"high52"];
NSNumber *low52 = [stockData objectForKey:@"low52"];
NSNumber *open = [stockData objectForKey:@"open"];
NSNumber *eps = [stockData objectForKey:@"eps"];

float percentChange = [change floatValue]/[price floatValue];

[self.priceLabel setText:[NSString stringWithFormat:@"%-.2f", [price floatValue]]];
[self.changeLabel setText:[NSString stringWithFormat:@"%.02f (%.02f%%)", [change floatValue], percentChange]];

if ([change floatValue] > 0.0) {
	[self.changeLabel setTextColor: [UIColor greenColor]];
} else if ([change floatValue] < 0.0) {
	[self.changeLabel setTextColor: [UIColor redColor]];
else {
	[self.changeLabel setTextColor: [UIColor whiteColor]];

//update change with percentage

[self.highLabel setText:[NSString stringWithFormat:@"%-.2f", [high floatValue]]];
[self.lowLabel setText:[NSString stringWithFormat:@"%-.2f", [low floatValue]]];
[self.high52Label setText:[NSString stringWithFormat:@"%-.2f", [high52 floatValue]]];
[self.low52Label setText:[NSString stringWithFormat:@"%-.2f", [low52 floatValue]]];

[self.openLabel setText:[NSString stringWithFormat:@"%-.2f", [open floatValue]]];
[self.epsLabel setText:[NSString stringWithFormat:@"%-.2f", [eps floatValue]]];
[self.volLabel setText:[stockData objectForKey:@"shares"]];

What next?

Ready to get started?  Just download the free MobileFirst Platform Server Developer Edition, and get started.

Complete source code for this project is available on my github account at:

Series on Apple WatchKit Apps powered by IBM MobileFirst:





Say What? Live video chat between iOS & WebRTC with Twilio & IBM Watson Cognitive Computing in Real Time

What I’m about to show you might seem like science fiction from the future, but I can assure you it is not. Actually, every piece of this is available for you to use as a service.  Today.

Yesterday Twilio, an IBM partner whose services are available via IBM Bluemix, announced several new SDKs, including live video chat as a service.  This makes live video very easy to integrate into your native mobile or web based applications, and gives you the power to do some very cool things. For example, what if you could add video chat capabilities between your mobile and web clients? Now, what if you could take things a step further, and add IBM Watson cognitive computing capabilities to add real-time transcription and analysis?

Check out this video from yesterday’s Twilio Signal conference keynote, where fellow IBM’ers Damion Heredia and Jeff Sloyer demonstrate exactly this scenario; the integration of the new Twilio video SDK between iOS native and WebRTC client with IBM Watson cognitive computing services providing realtime transcription and sentiment analysis.

If it doesn’t automatically jump to the IBM Bluemix Demo, skip ahead to 2 hours, 15 min, and 20 seconds.

Jeff and Damion did an awesome job showing of both the new video service and the power of IBM Watson. I can also say first-hand that the new Twilio video services are pretty easy to integrate into your own projects (I helped them integrate these services into the native iOS client (physician’s app) shown in the demo)!  You just pull in the SDK, add your app tokens, and instantiate a video chat.   Jeff is pulling the audio stream from the WebRTC client and pushing it up to Watson in real time for the transcription and sentiment analysis services.