Internet of Things,Big Data, Cloud Computing : The Perfect Match

What Is Internet of Things and How Does It Work?

Big Data is quickly becoming the next big asset for many organizations.  It would not be surprising for organizations to begin selling data of all types, including the metrics, knowledge, and insights gained from the data accumulated and analyzed. Riding on this wave of Big Data is Internet of Things (IoT). 

Technology, along with low storage costs, is making it easy for organizations to process large amounts of data; as a result, a new trend is emerging known as “capture it all.”  Capture it all means collecting as much data about your customers’ product usage and behaviors as possible because the data collected may be useful in the future.  At a time when organizations are seeing the benefits of Big Data, IoT provides innovative ways of capturing data that can enhance these benefits.

Internet of Things is the concept that things (animals, people or objects) with a unique identifier can automatically transfer data over a network without human interaction.   There are a number of devices that can be connected to the Internet to create a network of ‘things’ that communicate with each other to make intelligent decisions.  This is nothing new; the concept of Ubiquitous computing and sensor networks has been in use for a long time.

Why the Buzz Now?

Four technology trends are fueling the IoT revolution and renewing interest, they include:

1.     Big Data: Big Data’s success is making people realize the value of data, including the ways to identify valuable insights from data once considered junk.   IoT deployments can produce huge amounts of data, as sensors are constantly sensing stimuli and triggering real-time events.  It becomes relatively easy for the data to get accumulated over-time and the big data ecosystem or platform makes it easy to process these huge amounts of data. 

2.     Cloud Computing: With the advent of Cloud computing, computing power and data storage has become cheaper and easier to store and process data in Cloud.

3.     Ubiquitous connectivity: With the increase in the usage of smart phones with data plans along with the demand for connectivity to the Internet over smart phones, the infrastructure has been upgraded. Many IoT architectures are piggy backing on connectivity of the smart phone.

4.     Low cost sensors: The cost of Wi-Fi sensors and devices is in gradual decline. Standards like Near Field Communication (NFC), and iBeacon are becoming mainstream and supported by smart phones. As a result, App Developers can use them to creatively build IoT use cases. These improvements in the Bluetooth technology, Bluetooth low energy or BLE, are also becoming a catalyst to the IoT revolution.  In addition to the above, the ability of improved sensors to discreetly capture data is also a stimulus.  

 

How Internet of Things Is Used Today

Internet of Things deployments implemented right have the potential to become Big Data's killer Application.  Refer to figure 1 for the architecture used for typical IoT deployments.

 

Sensors that allow sensing of events are delivered to the mother ship on the cloud via servers connected to the Internet.  Data from these sensors is communicated via BLE and temporarily stored on the smartphone.  The use cases and potential for IoT and Big Data is endless as well as incredible.

A number of products based on IoT are getting launched and also receiving overwhelming response and adoption.  Wearable devices like Fitbit, Basis, Smartwatch from Samsung, and Qualcomm are playing an increasing part in IoT awareness.   Google became an early adaptor of IoT with its’ acquisition of the Nest Labs – Smart Thermostat.  Also, Google is gradually getting into home automation with their set-top boxes, NEST, Google Fiber, and Smart watches powered by Android OS.  Currently devices like Fitbit continuously and discreetly capture activity levels and sleep quality and then transmit the data to cloud using the smart phone. The sensors in turn communicate the data to smartphone through BLE.  Just imagine if there is a way to start tracking blood pressure, anxiety levels, stress levels, and heart rate in a similar discreet manner.  We can have personal data that is collected about ones self and then used by physicians in predicting a change in daily routine that can be causing current health issues.  For example, if a patient is unable to sleep properly, having the data collected historically could be invaluable in predicting what could have caused the current problem.  Tools like GOOGLE Nest Smart thermostat, Smart Smoke and CO alarm constantly track or monitor the environment in the house including information about lighting, humidity, daily behavior of the home's residents, temperature, and air quality.  Smartphone apps like Easily Do also discreetly record day to day activities of the owner by simply keeping track of the GPS on the cell phone. 

Potential Uses for Internet of Things

Imagine a world where devices can talk to each other, communicate and exchange information, and make intelligent decisions based on the data collected. For example, if you are coming home from a workout and, based on the data from your Fitbit and Easily Do, information is communicated to Google Nest thermostat that you would be home in a few minutes.  This information can be used to make your house more comfortable and cooler upon your arrival.  Taking this example a little further. What if data is captured from many people and made available to researchers (After anonymizing of Personal Identification Information).  This captured data can provide researchers and scientists with valuable data to study and find correlations between activities/actions that cause people to be susceptible to diseases.  This data can then provide feedback to users who may be susceptible to a disease and allow preventive measures to begin. In addition, trends/patterns may be identified that enable researchers to identify the reasons for diseases like heart attacks and Parkinson’s.  In addition, many of us may have seen sci-fi movies where an Artificial Intelligence system talks back and gives advice by analyzing a situation. Those days may not be far off due to the way technology trends in regards to IoT, Cloud computing, and Big Data are coming together.

Internet of Things’ Future

Gartner predicts that Internet of Things will affect every industry.  As a result, finding top analytics talent qualified to manage massive amounts of data will be difficult in the years ahead.  A yearlong research project conducted by Accenture shows that the United States is projected to create nearly 39,000 new jobs for analytics experts through 2015.  Only 23 percent if these jobs will be filled by qualified candidates. Cisco’s CEO, John Chambers, predicts that during the next decade the impact of Internet of Things will be 5 to 10 times greater than the Internet was on society and believes that IoT opens up a $19 Trillion opportunity during the same period.

IoT is here to stay and will make Big Data even bigger.  Our challenge, as IT professionals, is to discover innovative ways to use this technology that will enhance the general population’s lifestyle as well as benefit companies bottom line. 

Software development principles for an engineering manager,architect and developers

1. YAGNI - You Aren’t Gonna Need It :
   The YAGNI principle says that do not build something just because it might be needed later. Basically it says that do not build any code/features in the product that are not currently needed. This prevents the team from spending a lot of time planning for some grand, imaginary and unknown future scenarios. This will save time as most likely you do not need it or what you actually need is quite different from what we foresaw. This prevents teams from over engineering something based on what we think we might need later on. It is based on the idea that things will change with time. The principle saves you time twice. First, you don’t spend it now on something that you might don’t need. Second, when you reach the time when you need it, you don’t spend time in rewriting and refactoring but write once and well.By no means YAGNI is against planning and thinking in advance, it only encourages taking stuff into consideration NOW but postponing the implementation to later on
   Ask the YAGNI question

   "What are the chances that You Aren't Gonna Need It?"
   
   

2. KISS - Keep It Simple, Stupid:
   KISS is a principle that states that everything should be done as simple as possible. Applying KISS principle helps teams from over complicating problems. In my experience in the world of software development, developers tend to relieve the boredom of routine jobs by implementing an over complicating solution even when there exists a simple working solution. It feels great and exhilarating to do that until someone else needs to fix, maintain or modify the implementation. I must confess that I myself have done that many a time. One of my mentors once gave me a good analogy that I will not forget...an expert is some one who makes the job at hand look how simple it is and not vice versa. When ever we get back to our own code and start scratching our heads that sure sign that something got complicated than it had to be. Do not use all the fancy OOP, threading, frameworks just because you can.
   It is very simple to Implement the KISS principle. Whenever we come across a solution to a problem ask yourself " is it really the simplest way to do it? "
   Just remember
   
   "Some of the world's greatest algorithms are always the ones with the fewest lines of code. And when we go through the lines of code, we can easily understand them. The innovator of that algorithm broke down the problem until it was so easy to understand that he/she could implement it.Many great problem solvers were not great coders, but yet they produced great code! "
   
   For further reading on KISS
   http://people.apache.org/~fhanik/kiss.html
   
   

3. DRY - Don't Repeat Yourself:
   DRY is a principle that encourages to automate/extract tasks/code that we seem to be repeating again and again. DRY is aimed at reducing duplication and having a single point of maintenance. This principle can be applied in also not generalizing an implementation as a framework before we come across the need to repeat it again and again.
   
   
4. Premature optimization:
   Premature optimization is a term coined for the practice of trying to optimize the code to run faster when the code/functionality to be implemented is in a fluid state. Do not forget the well know statement " get it right then make it faster”. Do not get hung up on writing a fast-optimized code before getting the functionality right. The rationale is that it is most likely that the optimization that might be done prematurely might account to less than 3% of the actual bottleneck.The following quote from Donald Knuth in "Structure programming with go to statements" summarizes the problem perfectly
   " Programmers waste enormous amounts of time thinking about, or worrying about, the speed of noncritical parts of their programs, and these attempts at efficiency actually have a strong negative impact when debugging and maintenance are considered. We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all-evil. Yet we should not pass up our opportunities in that critical 3%."
   
   
5. Principle of Least effort :
   The principle says that people and even well designed machines stop looking for better solutions once a solution that minimally matches the acceptance criteria is met. Applying the principle helps us to find the most effortless paths to solve problems. It promotes a quick and simple design over elaborate systems designed by committees.
   
   
6. The partew law of 80/20:
   The law in the field of software states that 80% of the user will use only 20% of your features. By understanding the rule and identifying the 20% of the features that 80% of the users use we can concentrate the resources and time on those 20% of the features to produce a better product.

Many senior developers and architects even though well versed with these principles tend to be applying them only when they feel like it and miss the spirit of these principles. As one of my mentor used to say the word is "Resume Driven development" , teams tend to over complicate , try new api's , frameworks and do a lot of wastage disregarding the business goals and objectives. This is the very reason and importance for the management team to be well versed in the field of the development to be able avoid this kind of wastage.