IoT Evolution Podcast Recap: Edge Computing Future
Edge computing has become a topic of hot conversation as the technology capable of supporting sensor-2-server data transport has matured. The realization of true edge computing is accompanied by a host of benefits, including real-time data transmission, maintenance needs and considerable savings for operational expenses. Is edge computing the cut-and-dry future? Ken Briodagh, editorial director with IoT Evolution, plays devil’s advocate on a recent podcast with FreeWave Technologies CMO Scott Allen. He asks, essentially, “If companies focus resources on the real-time data transport at the edge – sending small packages of data at a time in the interest of speed – are we losing the benefits of big data? Do we lose the information that big data sets can provide in terms of predictive analytics and, ultimately, machine learning if we discard bits and pieces of data at the edge that we’ve deemed irrelevant?” Listen to the podcast below for Allen’s response! Overall, edge computing has three main drivers: latency–our need to have the data in milliseconds; loss of communication–able to solve the factory problem without shutting down the entire plant; proximity–sensors in the field monitor the data back to the edge. Edge Computing Solution Depending on the industry, a mixed bag of both programmable and edge computing solutions is an answer to Briodagh’s question. In some cases, especially with the oil and gas industry, companies rely on a sensor-2-server stream of communication, where they need to have the information in real-time, and if there is a problem, be able to act locally and fix the issue before anything drastic happens. The network is a combination of radios communicating with sensors that pass the data to a gateway and up to a cloud system. The network uses only small data sets to transmit a continuous flow of intelligent, sensor-based information, optimizing bandwidth in situations where latency is crucial. Next for the Edge There will come a time when using edge technology will just become a regular line item expense needed to do business in this modern age. Some early adopters have already started using gateway systems as a cookie cutter roll-out for all future expansions. Many worry the cost of entry is still too high to integrate, even though the need for transmission is great. As our digital age grows, infrastructure complexity and the desire to implement the latest technology grow along with it. Altogether, edge computing is still in its infancy stage, so no one really knows what data we deem irrelevant today will be vital tomorrow.
Thinking Outside the Box with Sensor-2-Server Applications
When we talk about Sensor-2-Server (S2S) applications, we tend to lean towards examples of common industrial communication networks for industries like oil and gas, utilities and municipalities. These application solutions typically incorporate the transfer of data from edge devices back to a specific server for use cases such as pump and tank monitoring or SCADA systems. However, as Machine-to-Machine (M2M) communications transform alongside the adoption of the Internet of Things(IoT), the types of applications that require connectivity at the edge are virtually endless. If we step back and look at the big picture, it is clear the entire landscape of technology is changing. With these changes we foresee the decline of standalone RF technology. Decision makers need Big Data in to make intelligent decisions that will transform their business operations and save them time and money. S2S communication networks are designed to address this challenge by driving intelligent transmissions from a specific location back to the appropriate server with the necessary intelligence to drive action for change. As technology evolves to meet industry demands, RF technology must adapt to meet new needs. We’re already seeing this happen in the industrially hardened, wireless communications industry. Some wireless IoT communication solutions providers are offering platforms to host third-party applications in addition to creating the communication links for devices. Sensor-2-Server Solution Along with this widespread technology change, we have begun to see new and exciting ways that modern RF technology solutions can be leveraged in an S2S network. Here are some nontraditional real-life examples of S2S applications: S2S communications to connect satellite communication dishes in remote locations where there is little to no cell coverage. The solutions extend communications and create a single POC for all of the remote locations. Monitoring cold storage food at distribution centers for a large US Supermarket chain where the cold storage warehouses are 500 feet X 500 feet and are located several hundred feet away from the monitoring room. RTK base station communications to improve data and correlation for an Electric Car manufacturer. Remote access to GPS Stations for improved data transfer in order to complete ocean mapping. Irrigation control on golf courses. For most industrial organizations there is a clear push towards complete connectivity from the sensors at the edge of the network all the way back to the central server. We often talk about data collection for familiar applications in oil and gas, utilities and smart cities. However, the reality of today’s technology transformation is that any industrial communication network, regardless of the industry, will likely need to connect its edge devices and eventually program its edge through third party applications in order to take the most cost effective approach and drive intelligent operational decisions.
IoT Evolution Expo 2016 Recap
IoT Evolution Expo invaded Las Vegas this week by taking over Caesars Palace. The conference focus was to be a premier source of information needed to help drive your enterprise forward with the latest in IoT applications. A few of the tracks found this year at IoT Evolution included IoT Security, Fog Computing and IoT Enterprise. Overall this expo gave attendees the chance to listen to various talks and panel discussions, as well as hands-on demos on the exhibitor floor, and evening networking nights with industry experts and peers. Here are some of the posts during the event: Diving into the IoT Evolution sessions, we learn the weakness of our smartphone. Godfrey Chua, analyst at Machina Research, informs us that the smartphone can be a very weak link in IoT and M2M communications when it is used as a remote control. And…IoT Evolution continued with more panel discussions. Yann Kulp, VP SmartSpace North America with Schneider Electric tells us that, the panel with GE, Amazon, US Celluar and Argus Insights offered intriguing updates with the use of Wiser Air in your home and other Wi-Fi IoT applications. FreeWave was fortunate to participate this year on both the Oil and Gas: Pirates and Protection, as well as the Brown Field Round Table: What to do when it’s too late to start again panel discussions. The Pirates and Protection panel give us all a chance to dive deeper into the critical industries and what IoT secure options area available for these remote locations. My second panel of the night with the Brown Field Round Table gave attendees to hear real world case study examples of Sensor-2-Server implementation challenges with blending older SCADA systems with the latest IoT solutions for continuous real-time results. Time to see an IoT application at work! James Brehm & Associates tried their hand at capturing this IoT conference with virtual reality technology. A new solution from RICOH THETA. The 360 angle is best viewed prior to hitting up Margaritaville. Interesting to see the “Workspaces & IoT” concept discussed as well. Digital workspaces takes center stage at IoT Evolution as Global Workspace Analytics reports 3.7 million U.S. employees now work from home. Cynthia Artin with IoT Evolution informs us that,”while the IoT is arguably taking off faster in more industrial domains (factories, farms, transportation), and has the most “sizzle” in consumer domains (smart homes, smart cars, fitness wearables), there is new energy forming around IoT enhanced offices.” Now as this year’s IoT conference comes to a close, we remember all the ways IoT will change our enterprise and our life this year. One thing is clear, the more we innovate, the more we strive to become more efficient, automated and safety operated within fog computing and cloud applications. We hope you have enjoyed this week’s roundup, as always tells us about your IoT highs and lows.
IoT Top News: Fog Computing Influences Apps
This week BI Intelligence revealed the key benefits of fog computing along with a list of industries adapting this methodology. It is estimated that 5.6 billion IoT devices owned by enterprise and government will soon use fog computing for gathering and processing data. Let’s dive into some recent news from the past week and start by taking a closer look at the latest development in fog (edge or access layer) computing. Fog Computing in the IoT Forecasts industries and adoption benefits Edge or fog computing will become a priority as enterprise deals with the exploding amount of data waiting to be collected, sorted and processed. “The ‘Internet of Everything’ — all of the people and things connected to the internet — will generate 507.5 zettabytes (1 zettabyte = 1 trillion gigabytes) of data by 2019, according to Cisco. A deeper dive into this week’s top news show us a few IoT applications ready to change our world, from farmer robots to drones reconstructing car crashes. Robots are coming to a farm near you The cost of adding robots to agriculture still remains high, yet these IoT machines are threating to shake up the farming community around the globe. Sara Olson, Lux Research Analyst recently reported that, “However, the costs of many systems are coming down, while wages rise due to labor shortages in some areas, and the benefits robots bring in the form of increased accuracy and precision will start to pay off in coming years.” Drones expected to reconstruct car crashes The Justice Department has plans this week to start running tests gauging the ability of drones to accurately reconstruct car crashes. Jeramie Scott, director of the Electronic Privacy Information Center’s Domestic Surveillance Project suggests that, “There should be public, transparent policies spelling out specific use cases to “ensure law enforcement drones acquired for one purpose,” like crash scene reconstruction, “are not then used for secondary purposes that undermine privacy and civil liberties,” like mass surveillance of the public.” We hope you have enjoyed this week’s short round up. Next time you see a smart device at work or around town, think about all the IoT sensors, Wi-Fi, automation and smart applications that come together to bring you state of the art technology experiences, and ask yourself “what will they think of next?”
IoT Top News: Manufacturing Disruption
Industrial IoT continues to cause disruption; not just in manufacturing, but across many other industries as well. In the last few months we’ve been keeping a pulse on the state of digital transformation across the business landscape and have been discovering exciting new implementations of Industrial Internet of Things (IIoT). This week we’re highlighting the disruption Industrial IoT is instigating as product development and lifecycle management continues to evolve. Overcoming Three Key Barriers to Industrial IoT Industrial IoT has the potential to capture data in real-time, leverage big data analytics and streamline efficiency to name a few. So what’s hold back the industry? A major barrier has to do with culture of the operational technology (OT) organizations within the industry. The OT have a risk-averse way of thinking and see change as disruption, “Whereas IT is defined by constant change and innovation, that’s why it’s not unusual to see industrial automation systems in service for decades at a time with little or no change.” Bringing Smart Technology to Old Factories Can be an Industrial-Sized Disruption It sounds amazing to have robotic arms working together with the Industrial IoT. The reality is manufacturing is being disrupted by the implementation of IIoT. Mary Catherine O’Connor with the Wall Street Journal reminds us that, “Often plant managers can’t tell which sensor will most accurately collect the data they want from a machine without a series of test runs—a time-consuming process.” Product-Development Strategies in the IIoT Disruption The key to succeeding with IIoT disruption will be to focus on the new innovation of both product and software for the industry. Machine Design reminds us that, “IIoT is a disruptive force that will shape product-development trends over the next decade and beyond.” Relying on CMM to Keep IIoT’s Disruption Positive All the talk up to this point has been about the negative disruptive impacts IIoT is having on the industry. IIoT has the ability to drastically change manufacturing with a positive level of disruption introduced on the shop-floor. According the the American Machinist positive disruption can happen, “By using coordinate measuring machinery (CMM), machine shops or other manufacturers are able to capture the precise details of the geometry or surface conditions of a workplace. Working within IIoT, those manufacturers then are able to share such data between machines, exchange information between facilities, or with customers or suppliers.” Now we would like to leave you with this quick excerpt from Kevin Ashton, a British technology pioneer who co-founded the Auto-ID Center at the Massachusetts Institute of Technology (MIT) and inventor of the term “the Internet of Things.” How the Internet of Things Disruption Gains Traction – Extreme IoT We hope you have enjoyed this closer look at the disruption Industrial IoT is bringing to the table and what steps are being done to allow more implementation across the industry. Let’s us know what disruption you have seen with IIoT.
Difference Between Data Sheet Transmit Power & Data Stream Transmit Power
Image courtesy of Flickr Creative Commons You need to link a two production sites together in your IIoT network in order to move critical voice, video, data and sensor data (VVDS™) between the sites by deploying access points. So, you consider using industrial Wi-Fi Access Points to implement this short-haul, point-to-point (PTP) RF link between the two sites. Short-haul RF links out to 8 miles are very doable using industrial Wi-Fi Access Points with directional antennas. You evaluate potential Wi-Fi Access Points from their data sheet specs. This is given, and you select one. Now, there is one specification that is commonly misunderstood and leads to confusion when evaluating MIMO capable Wi-Fi Access Points and using them in either PTP or point-to-multipoint (PMP) IIoT networks as wireless infrastructure. Confusion and mistakes arise from the difference between the transmit power stated on the product data sheet and the transmit power of a single MIMO data stream of the Access Point. For example, a 3×3 MIMO Access Point data sheet states the transmit power is 27dBm for MCS4/12/20 data encoding in either the 2.4 or 5GHz band. This is typical, and not a surprise, but what is this transmit power really stating. The FCC limits and regulates maximum transmit power from an intentional emitter, e.g. Wi-Fi Access Points. For Wi-Fi devices, the limits apply to the aggregate transmit power of the device. In above product spec example, the transmit power stated is the aggregate transmit power for the 3 MIMO data streams. Still good? Yes. You have a Wi-Fi Access Point and the total transmit power is 27dBm. Now, you design your short-haul PTP link using Wi-Fi Access Points and directional antennas. What transmit power do you use in your RF link budget? 27dBm since it is the transmit power for the Access Point for the data encoding and the band you plan to use. Right? No. While 27dBm is the total aggregate transmit power for the Access Point, it is not the transmit power of an individual data stream. The individual data stream transmit power is roughly 5dB less than the aggregate transmit power found in the data sheet for a 3×3 MIMO product. Difference in Transmit Power versus Aggregate Power 1 Data Stream transmitting at 22dBm — Aggregate Transmit Power is 22dBm 2 Data Streams transmitting at 22dBm — Aggregate Transmit Power is 25dBm 3 Data Streams transmitting at 22dBm — Aggregate Transmit Power is 27dBm So here it is… If you use the transmit power from the data sheet in your RF link calculation without correction, your actual link distance will be approximately half what you expect for the planned fade margin or the link reliability will be less than what you expect for the planned link distance. When designing RF links for the IIoT networks, make certain you are using the correct transmit power in your RF link budget calculations.
Sensor-2-Server: Intelligent Communication at the Access Layer
*This is the first in a series of blogs examining Sensor-2-Server communications, development and implementation. Throughout history, industrial revolutions have hinged on the power of automating processes. While automation today offers many benefits, imagine if you could automate thousands – or even millions – of processes simultaneously? This is the next potential wave of innovation, and it’s the organizations that are “geographically dispersed” or “automation heavy” that will benefit the most. While long-range communications and connectivity have become increasingly easier to attain, businesses need to be able to break down their isolated islands of automation in industry to achieve comprehensive and connected automation at scale. For example, there always has been a clear line dividing operations technology (OT) and information technology (IT) networks. The emergence of the Internet of Things (IoT) blurs that line as industrial operations head in the direction of complete connectivity for all devices on a network – including those remotely located in the field. With new dedicated access layer platforms, IoT data can be analyzed, acted upon and transmitted from anywhere in an Industrial IoT (IIoT) network. The increasing shift toward Industrial Internet of Things (IIoT) tends to bring up a lot of questions about the continued value of Supervisory Control and Data Acquisition (SCADA) systems that have traditionally served as the driver for monitoring and control in industrial markets. Although OT and IT are beginning to converge, there is still high demand for SCADA data. However, new technology offers the opportunity for data to be used in ways that were previously not possible, such as predictive analytics. This doesn’t make SCADA obsolete, as many operators are using it and will continue to employ it. Going forward, industries will leverage new technologies designed to help them make better business decisions than with SCADA alone. Sensor-2-Server™ (S2S™) intelligent communications for the access layer can collect and transport the data that supports higher-level analytics. As IoT becomes adopted by industrial markets, there is going to be an increased demand for video, voice, data and sensor data communication from the outermost layer of the network (think sensors on oil pads or water tanks). Industries like oil and gas, electric power, agriculture and utilities are starting to pick up on the benefits of S2S when it comes to profitability and cost savings through more advanced data analytics. Defining Sensor-2-Server S2S is intelligent communication that begins at the sensor level and targets servers for specific reasons. These servers could include anything from a SCADA data server that collects and monitors through the SCADA system or a Big Data engine. S2S could be leveraged in a predictive analytics engine that compares data at rest stored in a database to data in motion in real time from the access layer of the network. The concept of S2S extends beyond transmitting data. It is about creating intelligent transmission from a specific location back to the appropriate server with the appropriate intelligence to drive action for change. What is the Access Layer? The access layer is the edge of the IT network. An IT infrastructure has a core that is home to all the Big Data and data analytics. At this core, the data is “at rest” because it has reached its final destination. Next is the distribution layer of the IT infrastructure which is where the major plants, sites and facilities are located. Further out is the aggregate layer where data at the next level in the network is collected. Extending out even further is the access layer. The access layer is the layer at the far edge of the IT network. In oil and gas, for example, oil pads would be part of the access layer because they are typically remotely located at the edge of the network. It is highly likely that sensors physically exist in this layer for monitoring and control of these devices. Additional examples of the access layer are tanks, refinery sites and ocean exploration vessels. In water/wastewater, the access layer could be the treatment facility that has the water meters, pumps, smart meters, etc. Essentially, in an industrial site, the S2S access layer is the furthest point at which the operators are collecting sensor data. Industrial organizations today need intelligent secure communication and transmission from the sensor data back to the appropriate server, and there are a number of available options. What’s Next? Next week, we’ll continue our Sensor-2-Server series with a look at implementation and some of the core tenets of communication system development.
