Programming for Cloud-to-Device Communications in Industrial IoT

Should you leave processing in the cloud or on the edge? Both. Particularly in IIoT, developers need to start thinking about both tracks. There is a power struggle going on in the Industrial Internet of Things (IIoT). Many think cloud applications are the future of real-time data processing in IIoT settings; others believe data should be processed and decisions executed at the edge of the network. In truth, the answer lies somewhere in the middle: Data needs to be processed both via the cloud and at the edge, which presents an interesting opportunity for software developers in the IIoT space. Clearly, being able to operate industrially hardened smart devices remotely – and in many cases automatically – from the cloud presents many benefits. But the challenge lies in potential connectivity issues when developing applications. Developers must think along a dual track, which means that they must think about how an app developed for the cloud can be mirrored to run on the edge device itself. Several factors converge here to create a unique atmosphere for developers: connectivity, security, and today, the programmability of edge devices. Traditionally, the devices themselves simply acted as conduits for data collection and transport, but today, hardware manufacturers are creating devices that can host third-party applications. A point worth noting is the advent of Node-RED, which can streamline some of the programmability challenges. So, understanding the need for mirrored applications, let’s look at a few use-cases that highlight exactly why this redundancy is necessary. Cloud-to-Device in the Oilfield In the case of oil fields, when the edge app sees an oil pump showing a temperature reading above a predetermined safety level, the applications on the device can decide to shut the pump down, or the cloud application can send a command to do so. In cases where there are emergencies, different sites might have a different set of actions that need to be initiated. In fact, most sites have thermal sensors on the oil pads. If the oil pads exceed a certain threshold, then these cloud programs know there is an explosion and a fire happening onsite. To prevent a chain reaction, the cloud will send a command to shut down all the pumps and all the valves in that area so they don’t create a chain reaction and keep spreading. Extending the oil site example, if there is an intentional attack on the site, the first thing you do is disconnect the communication lines back to the cloud to protect the network. In that scenario, having the same application running on the cloud and the edge devices still allows the same decision to be made in the local network by the device itself. If the device cannot ‘see’ the cloud, it can still respond and execute tasks. If the cloud program is not responding, and the device notices the pad temperature goes beyond the threshold, it can initiate a local shutdown protocol. Once the network is back online, the device can send this information back to the cloud which can, in turn, be given to site operators remotely. Because of these necessary duplications, programming for these settings can be difficult. For example, in Oracle applications, in SCADA networks, all of the applications run on Java. Oracle pages run on Java. Therefore, most programmable industrial devices must demonstrate that they can run the same Java application locally. Many IIoT platform providers have now expanded the scope of the programming. They’ve built devices that can actually drag and drop the same Java code from the cloud into individual edge units, to run that device. Of course, it has to be developed for a device and for the cloud, so it requires some extra attention, mainly because on the device, the decision-making is slightly different. It does not execute the application unless it cannot speak to the cloud. When it cannot speak to the cloud, then it executes the command just the way the cloud would. Redundancy Applications in UAS In other industrial settings – unmanned systems, for instance – the protocols are different. If a drone can’t communicate with the operator, it could have a simple command that says, “Trace back all your GPS location and fly them in a reverse mode and go back to where you came from, until you can establish communication and get new commands.” So, it’s the same concept. Programmable IIoT platforms are now being set up and designed so that they can run applications in multiple different languages. If the application is written in C, Java, Python – basically, anything that can be read on the cloud – it can be dragged and dropped into those edge units, and it could execute the same protocols directly on the edge device. This simple concept is transforming the way the IIoT thinks about data transport and real-time decision-making. If you write your code once you can drop it in both places, and if the device loses communication, it knows what to do. Of course, there are many other considerations when thinking about programming applications for the edge and the Industrial IoT. Security remains paramount, and we see examples every day pointing to a potential meltdown if security isn’t addressed properly. Still, the potential for the cloud-to-device communication and application execution remains great. For developers, being able to think across platforms, languages and program functions are three key points to consider when creating applications for the Industrial IoT. This article originally appeared on

Robotics & IoT Merging Together

The Internet of Things (IoT) has made its appearance in a substantial number of industries, most recently manifesting itself in the the realm of robotics. IoT technologies and standards open the door for new robotic capabilities that are powered by cloud computing, communication with other robotic systems and sensor input from the environment around them.  Recent research has pointed to a new opportunity for robotics to operate beyond the scope of what was possible just a few years ago. As we look at a future of data and connectivity at every end point – from our cars, to our homes, to our businesses – it’s clear that we’ve just begun to scrape the surface of what is possible with the rapid expansion of IoT throughout the world. In a recent report, ABI research coined the, “Internet of Robotic Things (IoRT),” defining the concept, “where intelligent devices can monitor events, fuse sensor data from a variety of sources, use local and distributed ‘intelligence’ to determine a best course of action, and then act to control or manipulate objects in the physical world, and in some cases while physically moving through that world.”  The research certainly backs recent claims that robotics are going to leave a significant mark on the IoT industry. Take a look at the key statistics that Forbes recently reported on Robotics: 4% of developers are building robotics apps today. 45% of developers say that Internet of Things (IoT) development is critical to their overall digital strategy. 4% of all developers are building apps in the cloud today. RF Technology in the IoRT World As the entire technology landscape changes it is more important than ever for RF technology to adapt in order to meet new industry demands. Manufacturers in the hardened, wireless communication industry have taken note and set their eyes on all things IoT by developing Sensor-to-Server (S2S) communication solutions. Some of these wireless IoT communication solutions providers are offering platforms to host third-party applications in addition to creating the communication links for devices. This is an entirely new class of wireless IoT communication solutions that has the staying power needed in the midst of technology evolution. Robotic IoT Future Some companies using wireless S2S solutions, have already begun to incorporate IoRT into their networks. Real-life use case examples of robotics for IoT networks that are in the works today include: Semi-autonomous robotic geophysical surveying platforms for detection of unexploded ordnance. With an S2S communication solution, this use case will provide real time kinematic base station GPS corrections and combined geophysical data to a mobile command and control vehicle for concurrent advanced data processing by rear support group linked by MiFi or Satellite communications. A ‘ship-to-shore’ link for an ocean going wave-powered autonomous robot. As robotics systems adapt to the new technology landscape, they will increasingly integrate with IoT networks. With these new advanced robotics capabilities, businesses will see new opportunities for automation and efficiency to further advance operations and will be able to leverage this new technology for competitive advantage.

Top Industrial IoT News Roundup

There is a lot happening in the industrial IoT (IIoT) space lately, as evidenced by all the recent news announcements, analyst insights and business transactions occurring on the daily. Some say there is a foggy forecast for the industrial internet of things, mainly because the success of cloud computing must extend beyond data centers, but real world use cases should continue to pave the way. In some respects, perhaps it’s just the fact that the ROI from the IIoT is still in its infancy, but many are clamoring that a more standardized infrastructure is needed to help solve the unique complexities that IIoT presents. In this week’s IIoT news roundup, you’ll find a little bit of everything – from oil and gas and manufacturing to fog computing, drones and sensors. Dive in and see if you have any other articles that you think are worth adding! And don’t miss the bonus update at the end of the news roundup. Deloitte: End-to-End Automation Real Value of IIoT Technology By @KarenBoman | Published on @Rigzone “Industrial Internet of Things (IIoT) technologies such as machine learning and drones are now available, but the real value lies in linking these technologies together to allow for end-to-end automation, a Deloitte executive told attendees at the Internet of Things Oil and Gas Conference 2016 Wednesday in Houston.”   Is Now the Time to Apply Fog Computing to the Internet of Things? By Dr. Vladimir Krylov @Artezio | Published on @IoTEvolution “With fog computing, latency is minimized if one uses fog nodes for data analysis without sending it to the cloud. All event aggregation in this case has to be performed in the distributed architecture deployed in the network where devices (sensors) and fog nodes are located. Thus, fog architecture moves the capacity question from the cloud to the network implementation.”   Manufacturing firms investing in IIoT data analytics – even if other areas are slowing down By @James_T_Bourne | Published on @IoTTechNews “The research, the findings of which appear in the report ‘Data’s Big Impact on Manufacturing’, found that of the more than 200 North American manufacturing executives polled, 70% said investing in data analytics would lead to fewer equipment breakdowns, while less unscheduled downtime (68%), unscheduled maintenance (64%), and fewer supply chain management issues (60%) were also cited.”   Go Ahead, Fly a Tiny Drone. The Man Doesn’t Have to Know By @luxagraf | Published on @WIRED “THE WILD WEST days of drone flight came to end earlier this year when the FAA began requiring that pilots register their aircraft with the agency. If you want to use your Unmanned Aircraft System (as the FAA calls them) for anything remotely commercial, you’ll need to go a step further and pass a test.”   Could Optical Fibre Sensors Save Lives? By @loctier | Published on @euronews “This edition of Futuris looks at how optical fibre sensors could help monitor the stability of roads, buildings, bridges and other constructions – and save lives.”   Discovering Value in the Age of IIoT By @lasher64 | Published on @automationworld “The solutions of tomorrow will be much more integrated between implementation tiers on the plant floor to the enterprise and beyond. Therefore, it is imperative that these solutions give strong consideration to network architectures and cybersecurity. As we continue to move forward, you will hear more about operational technology (OT).”   IoT is not about radios; it’s all about data By Alan Carlton | Published on @NetworkWorld “The initial challenge for the Internet of Things (IoT) was how to provide physical connectivity of small and often remote devices to the Internet. This issue has basically been solved with the plethora of wireless connectivity solutions. The real challenge for IoT is data organization, sharing and search on an unprecedented scale.”   BONUS NEWS   This week, FreeWave announced a contest at a chance to win FreeWave’s award-winning WavePro WP201 shorthaul and Wi-Fi solution. Contest entrants must provide a high-level account of the application of the WavePro, along with a description of the need for the platform. Winners will be announced at the close of the entry period. To enter the contest, please visit:  Submissions are due by September 30!

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