While working on a recent iOS project in which an iOS app connects to a Bluetooth device, we discovered an issue: the connection between the app and the Bluetooth device could not be re-established if the app was terminated unless the user manually relaunched the app. Our Bluetooth device was turned on and off periodically throughout the day, so it was essential that it was able to reconnect automatically, even if the app was in the background or had been terminated.
Grio was recently asked by Soundwater Technologies to add Spanish and Portuguese translations to their iOS and Android mobile applications. The app pairs with Soundwater’s hardware to use ultrasonics to measure water flow. This project was a large undertaking, but it could have been avoided: if internationalization and localization patterns had been used during the initial app development, the process would have been nearly instantaneous.
App development is a field that has undergone rapid progress over the last decade. As new technology enters the field, the preferred tech continues to grow and change. Today, I want to discuss one of the more recent development tools to enter the market: Flutter.
A year after unveiling CoreML, Apple introduced CreateML. CreateML allows developers to train machine learning models on their Mac. We will stick with our previous example and build a simple machine learning model that can recognize images of dogs. Head over to https://github.com/RichardBlanch/Dog-Classifier/tree/Starter and download or clone the project.
In this post, I propose a pattern for allowing apps to transmit data through unstable network connections. I’ll be taking advantage of the modern architecture present on the iOS Platform, as well as the popular AFNetworking (or AlamoFire). To follow along, you’ll need some knowledge of iOS Native Development, NSOperation API, CoreData, and Networking.
“WHAT THE HECK?! HOW CAN I UNLOCK MY PHONE WITH MY FACE?!”
Those were the words that came out of my mouth in October of 2017, as I pored over the user manual for my new iPhone X. It wasn’t all hyperbole, either — I really wanted to know, and I ended up dedicating quite a bit of time to learning about the science behind Apple’s new facial recognition technology. In the end, the answer to my question boiled down to two words — machine learning.
A mobile app is a great way to bring new ideas to life, add value for your customers, or boost awareness of your business—but only if you can build a quality mobile experience without breaking the bank. And nailing down the cost of an app in advance isn’t exactly easy. App development costs can range from trivial to extreme, depending on a host of factors such as what your app does, how users will interact with it, and how you plan to staff the project.
These days grocery stores are facing many challenges, like high maintenance costs, price competition with online stores, and limited business hours. All of these issues can be solved with unmanned grocery stores.
If you are building a mobile application of any sophistication, you are likely to need some services to support your app. You’ll need a way to distribute your app for testing prior to submitting to the app store(s), as well as analytics, error logging, crash reporting, and possibly user and data management services. Of course, you could write these services yourself and provision servers to host these services, but why do that when you don’t have to?
Your company needs a mobile app and you want to save money (of course). You want the app live last week, and you’d really like to avoid hiring Android and iOS devs on top of your existing web team.