Internet of Things Ready for Takeoff

What Problem Trying to Solve

One new technology finding its way into the mainstream is called “Information of Things”, or “IoT”.  This cutting edge technology’s main function is to access connected devices to a central hub.  Data flows back and forth from embedded sensors out in the wild.  The small packets of data, contained in messages, from sensor to central hub, contain pulses of information.  Each message gets stored, analyzed, are fires an event trigger downstream for some action to occur.  The messages typically flow through the Internet, as well as Radio Signals, although no specific protocol has been established.  This segment of technology has potentially to create a planet of connected devices, flowing information, in real time, to improve customer experience, reduce costs and provide new applications and services. 
IoT is a disruptive, cutting edge technology.  By connecting devices to the internet in real time, we can manage millions of devices by communicating with billions of messages.  In order for that to happen, we need to have a framework in place.  That framework consists of a few key components.

IoT Components


Sensors reside in a variety of products today.  For example, home thermostats capture key metrics and report them back to a central hub.  That information gets stored and can be accesses via applications on websites, tablets and mobile phones.  However, some of the sensors are proprietary to specific Vendors. 


Vendors are typically responsible for the hardware devices.  And some devices contain proprietary sensors and software applications, which can be “black boxes” in that the programmers can’t see what’s going on under the hood.  And some hardware devices may not work with other Vendor products.  And some of those hardware devices fail over time and need to be replaced.  Perhaps years from now.  Will each Vendor still be in business then, if not, how will the device get replaced or repaired?

Embedded Sensors

The main premise behind the Internet of Things surrounds the idea of embedded sensors that reside within devices.  These sensors capture metrics in real time.  Those metrics are specific to each type of sensor.  A home thermostat might capture the temperature in Celsius or Fahrenheit, the humidity level, the date time stamp, how many people are in the room, energy consumed in specific time duration and a lot more.  Sensors that reside in airplane engines may capture millions of data points per minute.  It’s important to have the metrics sent back to the central hub, for storage and evaluation.  How does that information get sent there?

Operating Systems

Each sensor that resides within a device must be able to run software.  The software must run on an “Operating System” or “OS”.  The operating system must be able to run independently and receive updates and patches over time.  The central hub communicates with each device for troubleshooting, repair and reboots.  Think of the Mars Rover, that runs on another planet.  It runs independently, yet captures metrics for transmission back to earth.  NASA has the ability send commands to the Operating System to initial reboot, place in sleep mode or send updates to the OS to fix bugs.


IoT sensors capture data points and flow them to the central hub.  They use a message “protocol” to push and pull data packets.  The messages conform to specific structure, size, credentials to ensure they reach their destination.  Messages can be encrypted to prevent unwanted eyes scanning the data.  Typically, the message systems over the internet, using specific Protocols.

Data Storage

The incoming message need a place to reside once it reaches the central hub.  In most cases, the data is stored in a data repository, such as a Relational Database.  However, due to the high volume of incoming data, Hadoop is used to store the data across low end commodity servers using distributed architecture.  Likewise, due to the huge volume potential, as in millions of transactions per second, sometimes the data is scanned as it flows in and never stored off for later retrieval.  This technology is called Streaming Analytics.

Streaming Analytics

Streaming Analytics scans incoming data to look for patterns or outliers.  An outlier may be an anomaly or deviation from the norm.  This could initiate a predefined alert to perform some action.  It can also call another alert.  For example, perhaps one metric indicates a failed part within a device.  This alert could kick off a job to see if the issues exists within similar parts.  And perhaps check the Vendor data to see if a product recall was issued.  And if the number of failed units exceeds a certain threshold, perhaps issue a warning to other customers with similar units by issuing an email alert or text.  Or perhaps, the issues have already been identified and a corrective patch created.  The action could be to push a software patch to the failed device to correct the issue.


Embedded sensors out in the wild need a mechanism to flow its data to the host server.  One way to accomplish this is through the Internet.  Perhaps a device is connected to a Wi-Fi device residing within the home.  As the metrics are captured, messages can be routed to a switch, which flows only the relevant data to the central hub, to reduce overhead network bandwidth.  Some vendors use radio frequency as their main mechanism to flow data.  Ultimately, there needs to be a connection between the two endpoints.  Some connections don’t need a constant handshake to be open all the time, they simply send small packets of data as they occur or at specific time intervals.  However, other connection must be constant, in that they maintain “state”.  That ensures a communication between central hub and devices out in the field, for whatever reason.  Also, the networks can be secured to ensure no holes are exposed to hackers within the home network as well as people snooping the data packets as they flow across the world on the internet.


In order to get the Internet of Things applications created and operational, a software package can be purchased off the shelf.  Likewise, teams of developers can also write their own custom software applications.  When doing so, they pick a language they know, that meets the criteria for the application specifications and can support going forward.  Internet of Things applications can be written in a variety of languages and it just depends on your team’s skill set at the time.  Or you can outsource the IoT project to a consulting firm who specializes in such projects.

IoT Adoption Obstacles


Security has recently been addressed as a potential flaw in the adoption of IoT.  Unfortunately, any software can be hacked and any device connected to the internet can be penetrated.  With all the devices and all that data flowing back and forth, there’s a potential for security hacks and data breaches along the way.  The IoT device you installed to monitor your garage door could in fact expose your home network for infiltrators to get in, read and copy your files or install malware or Trojan horses.  Recently, people have discovered IoT devices that are not locked down nor encrypted, resulting in wide open networks.  There’s even a site that shows live mobile cameras in real people’s homes, to the entire world, without the users knowing.

No Standard Protocol

There is not definitive message protocol ensuring strict security, any Vendor can implement any system bypassing any security measures.

Shelf Life

If we look at an IoT application put in production today, what happens five years from now.  When the Vendor who manufactured the sensor is out of business and it becomes difficult to find replacement sensors when they go bad.  Same with software patches, operating system updates and hardware malfunctions.  How much time, effort and capital will it cost to revamp pieces of the IoT system five years from now when technology has pivoted in a different direction?

Lack of Qualified Developers

The world of IT is exploding.  There are new products and services released every single day.  Finding people with the right talent and skills to architect, create and maintain an end to end IoT system is not an easy task.  And what if the project has turnover where developers enter and leave the project.  How does the knowledge transfer occur and retained in-house?  How do you find people with architecture skills, software development skills, database skills, streaming analytics skills as well as network, hardware, operating system and message protocol skills?  Perhaps teams are assembled to bridge the gap of multiple skills.


An Internet of Things application can touch many pieces of an organization.  The software architects design the system, the network administrators configure networks, new servers have to be configured, databases created, connections to devices, Vendor agreements, Service Level Agreements, Quality Assurance people, Operations, Business Units, Sales, Accounting departments.  An entire plethora and assortment of people, places and departments.  So who owns the application.  Again, perhaps a team of departments or perhaps a new role, “Chief Internet of Things Officer”.


For the IoT adoption at massive scale, as in billions of devises, we’ll need a good mechanism to power the devices with minimal energy supplies.  Although some devices are microscopic in size, they still need some way to maintain power 24 hours per day.  And how do we service all these devices out in the field when their power supply goes out?



One of the nice features about the Internet of Things is the ability to have constant communication with devices out in the field.  To provide better quality service and custom fit your product to your customers.  And having the ability to automate the entire process is a huge benefit.  Potential cost savings, increased revenue by increasing customer base, as well as offering new products and services.  And potentially reducing staff.

New Data Sources

IoT allows organization new data streams.  This data can be stored forever.  And it can analyze on the fly or two years from now.  To look for patterns and identify key pieces of insight.  Also, the ability to link the IoT data with internal data sets of bump it up against external data sources.  Perhaps we notice an increase in energy consumption based on patterns in the weather.  How can we improve our product or service based on that piece of information?  We can derive insights over time by studying the patterns.  One way to do that is through Machine Learning.  Supervised Learning can detect patterns.  And Unsupervised Learning can learn over time with minimal human input.

Reports and Dashboards

Having new data sets allows new reports and dashboards to be created.  For consumer consumption in real time via a variety of devices.  And two-way communication allows users to make changes to IoT devices remotely in real time.  This new reporting capability empowers its users.

Smart Homes & Cities

Imagine having control of almost any device in your home while on vacation or at the office.  Smart homes are popping up all over giving the homeowners offering new levels of service and products.  Smart cities would allow constant and interactive communication while walking down the sidewalk or driving down the street.


Sensors can now be purchased to monitor basic metrics for the human body.  They can track the number of steps you take each day, your heart rate, blood pressure and you can view the results on your smart phone.  What if healthcare professionals had access to this valuable information for preventive care instead of treating when you get to the emergency room?  Huge costs benefit potential.  These apps can monitor your sleep to look for sleep disorder patterns and solutions.  Lots of potential.


IoT technology is upon us.  Offering the ability to manage billions of devices and messages at scale.  To store the data indefinitely.  Analyze for insights.  Constant communication with remote devices.  For widespread adoption of IoT, perhaps we need to define specific standards, frameworks and protocols that are open source, non-proprietary and work with a variety of languages.  The IoT will continue to leverage the Cloud platforms, to centralize the hubs for flow of data.  As well as the interrogation of data for insights.  As well as storage.  Perhaps we’ll clearly define the landscape for IoT ecosystems to train the next batch of developers to create connected devices that scale, are secure and provide value at minimal costs and ease of maintenance.

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