How Internet Of Things And Augmented Reality Are A Perfect Match
How Internet of Things and Augmented Reality are a Perfect Match
The combination of the Internet of Things (IoT) and Augmented Reality (AR) is not only allowing enterprises to gather data and generate insights from it, instead, it is also delivering those insights to the right people at the right time to create maximum impact.
If IoT is the year’s blockbuster, then Augmented Reality is gradually becoming an innovation that lets workers easily gain access to what’s happening with their smart connected products. IoT generates the data required and AR assists in using that data optimally.
Internet of Things (IoT) and Augmented Reality (AR)
IoT uses its network of smart objects, sensors, and processors, and makes the entire process autonomously responsive by continuously gathering data, analyzing it and triggering the relevant and appropriate responses from the concerned entities.
For Instance, IoT-based inventory management system uses sensors and scanners to monitor the consumption and storage of materials present in a manufacturing facility. Moreover, whenever the inventory reaches depletion, the IoT-powered systems either place an order for replenishment or it notifies the concerned authorities.
Augmented Reality is integrated to provide workers the ability to access vital information. For example, the use of AR smart glasses in the logistics department is helping to sort the units and also helps to identify packages efficiently without struggling to read the printed tags or use hand-held scanners.
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In their latest feat of engineering, researchers at Stevens Institute of Technology have taken an ordinary white button mushroom from a grocery store and made it bionic, supercharging it with 3D-printed clusters of cyanobacteria that generate electricity and swirls of graphene nanoribbons that can collect the current.
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Know these to get started with Python.
Web Development has advanced over a period of time
Taking a Mobile First Strategy to Web-development
Changing trends in web design via web development
Java's Ongoing Popularity
The Era of Modern Web Development
Python as a first language: a roadmap to getting started.
I personally prefer Java as a first language. Put non-technically, it is a lot less convenient, so you get a more realistic idea of how computers work. Nonetheless, Python is an amazing language (with convenience as one of it’s values) so it makes sense as a gentle introduction. It’s also a popular language for data science and machine learning, so it’s great to have experience with.
The 3 ingredients you need to get started:
The Python Language Interpreter: when you write some code in a text file and save it as a .py file, the Python interpreter is what turns that code into commands that your computer can then actually preform. This is necessary.
An Integrated Development Environment (IDE): An IDE is like a helpful text editor for programming. Some basic features include auto-complete, typo and mistake catching, and automatic text coloring to make some parts of your code easier to find. This is optional but highly recommended.
Some learning resources: We’re going to need something about programming basics, problem solving in computer science, using an API, learning how to use google and stackexchange, data types, control structures, and then maybe an object-oriented programming intro, and eventually all the neat advanced features of the python language. Then we need to learn how to use Numpy (for scientific computing), Pandas (for easy data storage), and Tensorflow (machine learning!). Add some handy cheat-sheets for python, numpy, pandas, and Tensorflow, and we’re good to go.
Other posts will adress download, installation, and resources.
A curriculum:
Like I said up above, we need to know how to do the following. Save this and make it a checklist.
Learn to use google to answer questions about installing or using python, any packages, or computer science.
This also includes getting to know how to search Stackexchange, the website for coding questions n’ stuff.
How to install python 3 and get set up
How to install an IDE like Eclipse (with PyDev), IDLE, or Notebook++.
Programming basics: how does python work? What does the language look like? How does tabbing work?
Understand basic logic, including AND, OR, XOR, NOR, NAND, XNOR, Implies, and If…Else statements.
Variables: what are they, how do I set one and change it?
Basic math in Python.
Data types: what kinds of variables can I have? How does my computer store data? How do I use those types of data? What are the key commands and operations I know how to do?
Control structures: if, else, elif, for loops, while loops, break, continue
Methods! What are they, how do I make one, what can I do with it?
The open() command, the all() command, other neat built-in methods
<function name>= lambda <your variables>: <single line method>
Problem solving in computer science: now do fizbuzz.
What’s a package?
Importing packages, installing packages you don’t have with PIP
Using an API: how do I find one and how do I read it?
object-oriented programming in Python: what’s a class, how do I make one, how do I reference and instantiate one, methods, class vars, etc
Error handling: how to do exceptions
All the neat advanced features of the python language: iterators, generators, list comprehensions, enumerate, range, assert, with…as, etc.
Read through the Numpy API (for scientific computing), data types, matrices, stats, methods, etc. A short detour through scikit would be helpful.
Read through Matplotlib.pyplot API, plotting, plotting options, histograms, scatterplots, etc.
Pandas (for easy data storage), data frames, series, built-in operations on columns and rows, loading from a CSV, saving as a csv, apply, etc
Tensorflow (machine learning!) For basic stuff, shoot for knowing how to use the estimator package, which is discussed elsewhere on this blog. Also get to know the nitty gritty, including tensors, layers, tensorboard, etc.
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