The stories in this issue can be seen at our website www.rethinkresearch.biz

Automotive transitions and self-driving technology Delphi and Otonomo enter auto data marketplace arena The Impact of IoT on Enterprises/Operators As IoT orchestration gets urgent, Google’s Apigee buy will gain value Security Is BrickerBot the IoT Batman? Artificial Intelligence & Machine Learning Machine-learning decision making in question as law begins adoption Smart Home Wink claims 27% US homes smart, makes case for SHaaS Networks White Space Alliance moves closer with WiFAR, plays buzzword bingo Utility Transformation and Smart Grids SEPA and SGIP merge in bid for smart grid standards unity

Riot: tracking disruptive technology and its impact in industry

Riot Issue 154 13 April 2017

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By Alex Davies Delphi has struck a deal with Otonomo, an Israeli startup, to pop-ulate Otonomo’s cloud-based data marketplace with data gener-ated by Delphi parts and technology – which the UK company sells to many of the biggest automakers. This is a move to chal-lenge Here and TomTom, which have similar marketplace ambi-tions, and is looking to entice automakers with the potential for monetizing their data. The Delphi-Otonomo deal is very similar to those signed by Here and TomTom, although not involving the titanic silicon providers that are moving into the automotive sector – Intel (Mobileye) and Qualcomm. Delphi is a large supplier to the auto industry, with a current market cap of around $19.8bn. In terms of pure parts rev-enue, it sits behind the likes of Bosch, Denso, Continental, Magna, and Johnson Controls, but Delphi appears set on making some-thing of a corporate transition. As part of the Otonomo deal, Delphi will be making an undis-closed investment in the startup, and at the same time, Delphi al-so announced an investment in Valens – another Israeli company, which is best known for its HDBaseT A/V semiconductors, but which is moving into the auto market via IVI (In-Vehicle Infotain-ment) and ADAS (Advanced Driver Assistance Systems) chips. Previous to these, Delphi has also invested in Movimento, acquir-ing it and its OTA update expertise, as well as buying Ottomatika and the self-driving software that Delphi used in its coast-to-coast Audi trip. Delphi also announced a deal with Mobileye, to develop a self-driving vehicle, using Delphi’s Multi-Domain Con-troller and Ottomatika software, to provide a full suite of camer-as, radar, and LiDAR, in combination with Mobileye’s Deep Rein-forcement Learning tech – the algorithmic software that teaches the system how to drive.

These are new systems, so while the thousands of other compo-nents that comprise a vehicle are still an important market for Delphi to compete in, it does seem keen to look beyond the car – and into sectors where external technologies and companies begin to interact with new vehicles. This seems to include both

Automotive Delphi and Otonomo enter auto data marketplace arena

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the IVI systems, which will play host to the content provides and app-based services from the consumer sphere, as well as the plat-forms on which the data generated by the vehicles will be hosted and used. Previously, Here has been the company most vocal about the pos-sibilities of a data marketplace for automakers, although always with a view to incorporating other data suppliers and buyers that would be interested in the geographically positioned data streams – presented in its Open Location Platform. Here’s rival TomTom has also made a similar move, partnering with Qualcomm to use its Drive Data platform as a means of in-gesting data from vehicles into the TomTom platform, and also acquired Autonomos, a self-driving startup in Berlin to expand its capabilities. Here signed a data-ingestion deal with Mobileye – a very influential chip and software supplier that has been snapped up by Intel for $15.3bn. It’s worth noting that Intel holds a 15% stake in Here, too.

It’s early days for Otonomo, which was only founded in 2015. To date, it has secured $40m in investment, with $25m of that com-ing in that in the Series B round in April – of which Delphi was the lead investor (according to Crunchbase). Here and TomTom should have a considerable lead over it, and Here looks set to be strengthened by Intel’s involvement in Mobileye too. However, Otonomo says that it has nine automakers using its platform to date, with Mercedes-Benz parent Daimler the only publicly named company to date – and the extent of that deal in terms of models isn’t known. As a cloud-only system, it sits between the databases of the au-tomakers and the applications that wish to use the stored data, and uses a rules-engine to ensure that local data regulations are followed. This automotive data has clear value to the likes of insurance pro-viders and dealerships, for monitoring vehicle usage, but also to the automotive retail market that supplies vehicle maintenance and accessories. In addition, cars bring people to places, and so local businesses are interested in the potential value of usage da-ta in their marketing strategies.

It’s early days for Otonomo, which was only founded in 2015. To date, it has secured $40m in investment, with $25m of that coming in that in the Series B round in April – of which Delphi was the lead investor.

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Smart cities and traffic systems are other obvious stakeholders, which would want to use the data as a means of better planning new construction or adapting old roads to current usage – as well as simply better managing traffic and congestion in urban envi-ronments and highways. All of these applications represent a po-tential source of revenue for the automakers, on top of the reve-nue they generate by selling the vehicle in the first place. This is an important transition for the automakers to manage, as it appears that increased urbanization and the rise of ride-sharing services are going to put a dent in the sales of new vehi-cles. Consequently, automakers have to work out how to replace this lost or shrinking revenue via the vehicles they do manage to sell. Riot has written about this in a recent report, but the shift to Vehicles-as-a-Service will rely entirely on data.

By Caroline Gabriel As organizations in many industries start to make concrete plans for the Internet of Things (IoT), emphasis is shifting from visions of new use cases, towards the practical challenges of deploying large numbers of devices, often with high requirements for secu-rity, reliability and low latency. Many solutions in the first wave of IoT platforms for industrial and vertical market use have been mainly concerned with connecting the devices and collecting and analysing the data they generate. But now, many players are also focusing on the next step – how all those connected objects will communicate with one another. Google and others call this IoT orchestration, meaning multiple connected devices being “aware of each other and working to-gether”. This is not to be confused with orchestration in the soft-ware-defined networking (SDN) sense, which involves specific emerging standards and technologies. Those orchestrators cer-tainly will be used to coordinate and manage IoT networks, where the devices are attached to virtualized network elements. Google’s idea of IoT orchestration is related, but could be achieved with many architectures.

Enterprise & Operators As IoT orchestration becomes urgent, Google’s Apigee buy will gain value

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At a conference in Silicon Valley earlier this year, Wayne Pie-karski, a senior developer advocate for Google, said: “When you walk in your home, the lights come on and coffee machine goes on. People don’t want to control a single light bulb, they’re going to work with multiple devices, which means working with multi-ple manufacturers.” Currently, users have to buy one product and download its app, but companies like Google, looking to manage all these items from its clouds – and monetize the data – want to decouple the objects and the apps, so developers can easily work across differ-ent hardware as they do in Google’s Android world. Google has Android, Brillo and Weave as the basis of its attempt to drive an open software environment for the IoT, with the ultimate goal being its ‘physical web’ vision, now supported by an open source effort, in which all connected devices would work together with-out the need for separate apps. The issues of orchestration, cooperation and hardware/app de-coupling become more complex and critical when suppliers look outside the smart home – Google’s current main focus – to the Industrial IoT. Here, it may be critically important to resource ef-ficiency, performance, security and availability that connected devices are aware of one another and work seamlessly together. As the IoT spreads out from consumer into business- and even mission-critical enterprise services, expectations of reliability and availability will rise, and will be incorporated into service level agreements (SLAs). These SLAs will become more im-portant, and more demanding, as organizations start to exchange IoT data, driving orchestration and mediation from an internal IT issue to an inter-organizational one. Mind Commerce, which has recently published a report on the topic, cites Google’s definition of IoT orchestration, but adds to it, writing in a blog post: “Mind Commerce IoT Orchestration defini-tion: Balances and directs IoT resources with consideration to-wards the privacy and security needs of IoT resource owners/managers and the needs of resource requesting entities … A relat-ed and often interchangeable term, mediation, represents a func-tion that routes or acts on data/information passing between net-work elements and network operations.”

These SLAs will become more im-portant, and more demanding, as or-ganizations start to exchange IoT data, driving or-chestration and mediation from an internal IT issue to an inter-organizational one.

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Standards in these areas will be essential, or potential IIoT busi-ness cases may be stalled because there will be no uniform and fully trusted way to share sensitive data and ensure performance. The work may be done in open source, by conventional standards bodies, or by individual vendors. It is highly likely that Google will be a guiding hand, harnessing some of its existing assets, such as Brillo and Weave, and its acquisition of API platform Apigee. Apigee supports management, integration and orchestration of APIs (application programming interfaces) from its platform, along with associated predictive analytics. As such, it will en-hance Google’s cloud offerings, including its IoT systems. One of the most recent additions to its line-up was Apigee Link, de-scribed as an API-first IoT product for connecting devices to the Internet. Chet Kapoor, CEO of Apigee, said before the Google deal: “APIs are a critical enabler for the Internet of Things” and claimed the API-first approach, combined with Link’s end-to-end connectivity and mediation, would enable “any device maker to become a digi-tal platform business and to take advantage of the IoT.” It seems likely Google will move Apigee and Link to the heart of its work on IoT orchestration, especially as Link leverages the open source project Zetta, initiated by Apigee. That could feed into the search giant’s preference to work through open source programs in its quest to drive standards and so accelerate pro-gress in key technologies.

Standards in these areas will be es-sential, or poten-tial IIoT business cases may be stalled because there will be no uniform and fully trusted way to share sensitive da-ta and ensure per-formance.

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By Alex Davies A new and particularly nasty looking bit of malware has been spotted in the wild, but for once, it might not necessarily be bad news. Called BrickerBot, the code attacks vulnerable devices in the same manner as Mirai, but instead of commandeering them for nefarious purposes, BrickerBot tries to take them permanent-ly offline – acting as a dark-knight or a criminal, depending on whether you own the bricked device. Spotted by Radware, via its honeypot servers, BrickerBot exploits the Telnet protocol to brute-force its way into a device, in much the same way that Mirai operates. Radware wasn’t able to trace the attacks on its one of its trap servers, due to the strain using a Tor node to mask its identity, but another server spotted heavy traffic from Argentina. Radware noted that the versions spotted were distinct from each other. Named after its propensity to hunt IoT devices using the BusyBox toolkit, BrickerBot will target the device’s memory, running a whole host of code to render it unusable – limiting the number of kernel threads to just one process, disabling TCP timestamps, and running the always rather terrifying ‘rm -rf /*’ command. After this, it deletes the IP tables, firewalls, and network address translation (NAT) information, then blocks outgoing packets, and finally reboots. The end result is a completely unusable device – a Permanent Denial of Service, as Radware puts it, also known as phlashing. Any device that has Telnet enabled and uses insecure admin cre-dentials, especially those that ship with hardware-defined logins or very weak factory passwords, is potentially vulnerable to BrickerBot – but from where we sit, this is kind of a good thing, as it means it can’t be compromised by something like Mirai or Hajime, and put to use in criminal attacks. Devices that have been deployed in such a manner aren’t going to be patched any time soon, as any sysadmin or network engineer worth their salt would have fixed these issues pre-deployment. A device that is in the wild and still vulnerable to BrickerBot has

Security Is BrickerBot the IoT malware Batman?

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likely passed through some sort of systemic incompetence, one that is either unaware or unmoved to their potential risk. Attacks on critical online infrastructure today might lead to mild annoyance, as consumers find themselves unable to use online web services, or businesses begin finding that their overlapping online dependencies result in service outages. But while that might lead to lost dollars today, with the IoT, in a few years, we might be looking at a world where lives are lost, not just revenue. So the BrickerBot malware acts as a vigilante, removing vulnera-ble devices from the internet so that they can’t harm a wider community – but acting wildly outside of the law, ostensibly in the name of a greater good. Of course, for the device owner, its methods are reprehensible, but for those who are potentially saved by having vulnerable de-vices permanently take offline, such a system could be salvation. So could you ever legalize such a program, as part of the Ministry of Internet Security? It’s an interesting thought experiment, at least. What would happen if a country was worried about online security and decided to unleash such an attack on all IP addresses within its geographic reach, after passing a law to give it legal protection to do so, and fair warning to its citizens and business-es? Well, thanks to the global nature of the internet, not much would actually happen – as the country would still be vulnerable to at-tacks from abroad. So what if it cast its net wider, and unleashed such an attack on the world, and set it up to roam the web inces-santly? Could you ever get a global organization like the UN to agree to such a system? Last week, we spoke to Kentik’s Alex Henthorn-Iwane, who said that a federated anti-DDoS system would potentially solve a lot of problems in the networking business – with companies charging for their services in a similar manner to the chargebacks that MNOs use to handle roaming devices on their networks. An extension of this thinking would see a federated initiative to identify an quarantine vulnerable devices. Perhaps ISPs, both fixed-line and mobile, could be encouraged to add lines to their

The BrickerBot malware acts as a vigilante, remov-ing vulnerable de-vices from the in-ternet so that they can’t harm a wider community – but acting wildly out-side of the law, os-tensibly in the name of a greater good.

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Obama wants “No blocking No slowing down Fast intercon-nects, No priori-tization, Trans-parency”

Terms of Service, that would allow them to prevent vulnerable devices from accessing the wider internet – via a tool like Brick-erBot. Should insecure IoT devices prove worrying enough to govern-ments, we could easily see regulation passed to mitigate the dam-age that they might do. Given that consumer devices are continu-ously in a race to the bottom, in terms of BOM costs, security is an area that is going to be skimped on. As such, a country won’t have much luck trying to legislate to keep devices out of its borders, and so it would be better served by enforcing network-level rules, rather than device-level. But much like the market for devices, the internet is a globalized entity, and as such, it would be hard to draw a line as to where you stop hunting for insecure devices. There’s not much point se-curing the US if a European botnet will still happily knock the East Coast offline. With BrickerBot, a US ISP might find itself in hot water if it begins attacking devices in Hong Kong – even if Go-tham’s police department approves of the outcome. The BrickerBot authors are unknown, much like their motives. In some Mirai attacks, researchers observed that the code would alter the insecure credentials that had given them access, in order to prevent rival cybercriminals from gaining control – a sign of the competition for resources. As such, this could just as likely be an enterprising criminal looking to disadvantage their rivals by thinning the herd, or a digital vigilante looking to attack Mirai.

With BrickerBot, a US ISP might find itself in hot water if it begins attack-ing devices in Hong Kong – even if Gotham’s police department ap-proves of the out-come.

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By Alex Davies A series of announcements from law firms embracing AI-augmented systems has raised questions about accountability and adoption, spurred in part by the mysterious nature of ma-chine-learning operations. With the EU law considering a law that requires companies to provide explanations for their machine’s autonomous decisions, AI developers are entering unknown ter-ritory. There’s a distinct irony in an AI-assisted lawyer being undone by a law designed to hold it accountable, but what the EU is debating is a means of examining the decision-making process used by these neural networks. However, the complexities of these sys-tems make such a requirement potentially impossible to meet, as the machine-learning functions have essentially programmed themselves without human intervention. Of course, the developers begin with a process, and can tweak the system if it begins coming up with incorrect answers, but broadly speaking, once these systems begin generating consistent correct answers, they are a being unto themselves. While law-tech has already drawn some ire, with a couple of spoof press releases, the legal profession is just one of many that is well positioned to be highly automated – and Riot has recently published a paper on the kinds of technology that will power this transition. However, law is perhaps the most influential sector that is poised for high levels of automation – with its high levels of bureaucracy and document handling on the one hand, and its incredibly life-changing impacts based on both successes and mistakes. What assurances do the citizenry have that an AI-assisted judge and jury can make the right decisions? This is where the AI and law clash – while AI and ML are ways of more efficiently performing a process, both appear impenetrable to the common man. One wonders what checks and balances could be implemented to ensure that a legal system that is greatly augmented by AI-based processes would still be interpreting the

AI & Machine-Learning Machine-learning decision making in question as law begins adoption

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law correctly, especially if it is not possible to understand how an AI-based system arrives at its conclusions. As the MIT article notes (an excellent read), the researchers are essentially responding to an output, correcting the code or ad-justing an algorithm to achieve the desired outcome. However, while the can influence these components, the inner workings of the neural networks that they use in their machine-learning ap-plications are hidden from them. When discussing an Nvidia-powered self-driving car, MIT says that “the system is so complicated that even the engineers who designed it may struggle to isolate the reason for any single ac-tion. And you can’t ask it: there is no obvious way to design such a system so that it could always explain why it did what it did.” The article asks whether AI-based deep learning shouldn’t hap-pen until ways of making the technologies more understandable to their creators and more accountable to their user are found, and in the context of law, that’s a very sensible line to take. An-other talking point we have encountered in our research is that of military AI adoption, and the issue of how to hold a killer robot accountable for breaking the rules of engagement. Using the example of the Mount Sinai Hospital’s Deep Patient pro-ject in New York, which began crunching 700,000 patient rec-ords, the article noted that Deep Patient’s creators couldn’t ex-plain how it had begun to anticipate the onset of psychiatric dis-orders like schizophrenia – conditions that are “notoriously diffi-cult for physicians to predict.” As its team leader Joel Dudley put it, “we can build these models, but we don’t know how they work.” Which then raises the issue of accountability, especially when you consider how a hospital might defend itself against a lawsuit brought against it by a family that lost a child due to a misdiagno-sis by an AI-based system. The question then is to who do you as-sign accountability – the doctor who trusted the AI-system, the developer who designed it, or the system itself. Which brings us onto the recent spate of law-focused AI-based systems. The most prominent one is DoNotPay, a free service that used an AI-based system to power a chatbot interface that would

As Deep Patient’s team leader Joel Dudley put it, “we can build these models, but we don’t know how they work,” - which then raises the issue of ac-countability.

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help people challenge and overturn parking tickets. Developed by Joshua Browder, a second-year Stanford student, DoNotPay re-ceived a lot of coverage last year, after successfully challenging 160,000 of the 250,000 tickets that users submitted. The app would ask questions to determine if an appeal was possi-ble, before automatically carrying out the appeal process if it de-termined that it would be successful. With a 64% success rate, DoNotPay has appealed over $4m of parking tickets, and Browd-er plans on expanding it to work in Seattle, as well as moving into to flight delay compensation schemes, and refugee and asylum claims. Facebook has also experimented with chatbots, with a long-term view of monetizing its Messenger service by letting businesses use it as a platform to interact with customers – for things like customer service, bill paying, or even sales. However, its first for-ays were poorly received, with chatbots for CNN and the WSJ prompting online backlash for spamming users and not being particularly intelligent. For Facebook, its huge user-base represents ample opportunity for additional revenue streams, on the back of these chatbots, but it appears to have some way to go before its users see them suffi-ciently useful. Other law-focused bots include LawDroid, which facilitates the registration and incorporation of companies via Facebook Mes-senger. The system was built by Foresight Legal, a virtual law firm that operated in a distributed manner and that had previ-ously offered prenuptial contracts via LegalZoom’s portal and marketing. It uses Python to handle the document authoring systems that Messenger can’t provide, but is rules-based and doesn’t use ma-chine-learning functions – although v2.0 is scheduled to adopt that feedback mechanism. Elsewhere, BakerHostetler (BH) made the news for its use of IBM’s Ross AI, used to handle a bankruptcy practice. CEO Andrew Arruda said that BH wasn’t the first law firm to license Ross, and that other announcements are due soon, but Ross is “the world’s first artificially intelligent attorney,” based on IBM’s Watson.

With a 64% suc-cess rate, DoNot-Pay has appealed over $4m of park-ing tickets, and Browder plans on expanding it to work in Seattle, as well as moving in-to to flight delay compensation schemes, and refu-gee and asylum claims.

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Learning from the queries it is asked, Ross is primarily used as a research tool – to make trawling through legal records, rulings, and precedents a much more time-efficient process. The obvious advantage here is that more staff time is freed up to work on each project, but for the firm using Ross, the tool should become more useful and knowledgeable as time goes by – better anticipating and answering questions.

By Jack Vernon Smart home developer Wink has published a report that claims smart home devices are now in 27% of American homes. Howev-er, the report fails to define what qualifies as a smart home de-vice – leaving us not much the wiser, and still questioning the lack of progress in the sector. In addition, the claimed price just seems to build the case for operators to move in on the smart home, offered as a service to mitigate a high upfront cost – i.e. not the Wink route to market. This issue of what qualifies as a smart home eludes both this re-port and the consumers it interviewed. Some 34% of those sur-veyed believed that it would cost $5,000 for a house to be consid-ered a smart home, a further 9% thought that a smart home would require around $20,000. Evidently, these consumers believe a smart home has to be fully autonomous before it can be considered a smart home – some-thing like the effortless smart homes with dozens of devices that we see so often in the marketing vision. On this basis, this per-ceived cost of installation is going to be holding consumer inter-est back. But the report found that the average smart home owner has spent just $200 on four devices. There is a clear difference in what 43% of consumers consider to be a smart home and what the reports considers qualifies – those that think a smart home costs upwards of $5,000. It seems clear to Riot that $200 is no-where near enough to equip a home with enough tech to be deemed ‘smart.’

Smart Home Wink claims 27% US homes smart, makes case for SHaaS

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The vision of the smart home that is frequently pitched at con-sumers is pretty comprehensive, with devices in every room - re-quiring far more than the 4 connected devices that the Wink re-port deems as sufficient. In terms of devices per room, you might have door, window and light sensors - then a connected outlet, radiator, camera, thermostat, giving us a total of 8 devices per room. To achieve these levels of connectivity within the home, custom-ers will need to spend far more than $200. Take one application like lighting, where the popular Philips Hue starter pack only in-cludes two smart bulbs and its own hub, costing $70. Assuming that your house requires one light per room, the cost of smart lighting very quickly exceeds that $200 threshold. Wink doesn’t disclose the list of devices it considers to be smart home. Broadening the definition would help to increase the num-ber of qualifying smart homes, but there are questions over the legitimacy of this approach, if Wink was indeed trying to inflate the figures. The Amazon Echo, for instance, can control devices from ecobee, Nest, Honeywell, Philips Hue, SmartThings, and Wink, and we ex-pect many consumers to engage with these platforms through the Echo. But does the device itself actually qualify, as all it does is connect to the internet. If the Echo qualifies, then other voice recognition platforms like Siri should too. If that were the case, smart home device penetra-tion would probably be something like 120% - if you begin count-ing smartphones as smart home gateways. Smart home platforms are still a four-figure upfront investment, and involve installing several devices in each room of a custom-er’s home, often paying additional monthly service fees for things like cloud storage. Smart home devices are still expensive, and the price of the service has to either be bundled in the upfront cost, or covered by a monthly fee. For this reason, Smart Home as a Service (SHaaS) is likely to ac-count for most of the mass smart home penetration, in the early stages. Service providers like cablecos and ISPs are well-placed to move into SHaaS, as they already have customer relationships

Smart home plat-forms are still a four-figure up-front investment, and involve in-stalling several de-vices in each room of a customer’s home, often paying additional month-ly service fees for things like cloud storage.

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and can leverage a bundled SHaaS offering as a way to increase their ARPU and reduce churn. The report didn’t differentiate between the professionally in-stalled smart homes and the DIY approach, but for homeowners who have already taken the plunge, Wink found that US renters are prepared to pay 5% more for properties that include smart home devices. Insurers also appear pro smart home, lowering prices for customers that include things like connected smoke alarms and leak sensors in their homes. The report closed with the finding that some 175m Americans wish they could monitor what happens in their homes remotely - showing the strong potential of smart monitoring devices. Home security is a very popular first application for smart home adopters, but monitoring pets and children are other strong pur-chasing decision drivers. So while the current cost of a smart is still expensive, and likely to remain that way for the foreseeable future, it appears that the sector has a huge addressable market – once it finds a way to make it more affordable. This is why SHaaS makes a lot of sense, and while some devices like bulbs, outlets, or wall switches can be added to a smart home on an ad-hoc basis (via eCommerce or grocery shopping) the op-erators are can ensure they provide the core smart home net-work infrastructure – the hub or gateway, potentially via their consumer premises equipment (CPE).

While the current cost of a smart is still expensive, and likely to re-main that way for the foreseeable future, it appears that the sector has a huge ad-dressable market – once it finds a way to make it more affordable.

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By Jack Vernon The White Space Alliance’s (WSA) new WiFAR protocol has taken a step closer to launch this week, with alliance members Amer-iSys and Saankyha Labs publishing a test vector format for WiFAR – a long-range wireless protocol looking to take ad-vantage of the unutilized TV white space spectrum. The WSA is promising that WiFAR will be able to support a range of emerging applications, including machine-to-machine commu-nications, IoT, smart grid deployment and industrial automation. However, the announcement reads a little like buzzword bingo - trying to draw in as many potential developers as possible, but thankfully avoiding the AI and machine-learning claims that litter so many announcements these days. By announcing the test specification for WiFAR, WSA partners will now have the opportunity to develop IoT-based applications, and start to consider potential use cases. However, given that all the projects currently associated with the alliance are focused on providing broadband services this is early days for IoT applica-tions. But there is still strong demand for unlicensed spectrum, as it can often reduce the cost of an IoT deployment – by avoiding the monthly or annual fees that a network provider would charge. The trade-off here is that an adopter must invest in creating their own network, but WiFAR is at least positioning itself as a choice for developers, looking perhaps for a wireless backhaul technolo-gy more suited to moving large volumes. The WSA says it could deliver up to 22Mbps to 29Mbps over long distances, up to 30km from the base station. The group hopes the technology will be used to deliver rural broadband and bridge the digital divide in underserved communities. For non-broadband purposes, the WSA believes that WiFAR could serve IoT applica-tions, likely in niche deployments – not national roll-outs. WiFAR could be used in combination with other unlicensed op-tions, such as LoRa, acting as that backhaul option. The LoRa Alli-

Networks White Space Alliance moves closer with WiFAR, plays buzzword bingo

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ance has been successful in encouraging a number of major net-work operators to deploy its technology, as well as in niche local-ized projects. Rural deployments might justify the use of a wire-less technology like WiFAR, instead of paying for an LTE link or to install a wired connection. TV white space (TVWS) has not had an easy ride so far. The WSA has so far seen slow regulatory acceptance progress in many non-US markets. TV white space is a prime area of new license-exempt services, especially for extending low cost broadband to rural users, but setting up large projects in the spectrum is com-plicated – owing to the regulation, which differs according to each country. The WSA was formed in 2012 and has since been working on a specification based on the broad 802.22 family specs, first ap-proved in 2011. The aim of the alliance is to promote the development, deploy-ment and use of standards-based products and services as a means of providing broadband capabilities via white space spec-trum. The driving force behind the alliance appears to be Saan-khya Labs, a company which acts as a vendor of WiFAR base sta-tions, chipsets, and chip modules. The WSA is confident that once WiFAR reaches scale it can deliv-er internet access for the cost of less than $10 a month per house-hold. The equipment is cost-effective at this price because the technology allows base stations to be installed near ground level, not on towers – helping to keep the network installation costs down.

The WSA says it could deliver up to 22Mbps to 29Mbps over long distances, up to 30km from the base station. The group hopes the technology will be used to deliver rural broadband, and the WSA believes that WiFAR could serve IoT applications.

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By Alex Davies The Smart Electric Power Alliance (SEPA) and the Smart Grid In-teroperability Panel (SGIP) have finished their merger, hoping to become the single fountain of knowledge for utilities looking to move to smart grids and renewable energy. Continuing under the SEPA name, SGIP’s integration adds some 80 new members to the already thousand-strong SEPA base. SEPA has mostly focused on encouraging research and collabora-tion in the smart grid ecosystem, while SGIP has had Distributed Energy Resource (DER) Management and cybersecurity as its pri-orities. The merger announcement was first made back at DistribuTech, but the two boards have now passed the required votes to com-plete the deal. The next year will see them integrated their opera-tions in phases, with all SGIP staff joining SEPA. This isn’t the first merger for SEPA, which absorbed the Associa-tion for Demand Response, back in November 2015 when SEPA stood for Solar Electric Power Association. With the merger came a rebrand, with SEPA swapping Solar for Smart, and a move to focus on the integration of solar generation into utility grids and systems. As an educational nonprofit, SEPA aims to ‘facilitate the electric power sector’s transition to a clean energy future through educa-tion, research, standards, and collaboration.’ With the integration, SGIP’s focus on accelerating grid modernization and the ‘energy IoT’ through its policy, education, and interoperability standards, promotion will be carried on inside SEPA. The pair noted that while they had a lot of shared members, they were often working with different people inside those organiza-tions – so the new consolidated approach should grease the wheels. SEPA’s growth should help utilities navigate the complex process of merging their infrastructure and operations with their neighbors, as well as entering new ecosystems in smart home and smart city deployments.

Utility & Smart Grid SEPA and SGIP merge in bid for smart grid standards unity

19 13 April 2017 Riot Issue 154

Utilities and energy suppliers are currently in the middle of a sig-nificant transition period, as renewable energy like solar and wind have become cost competitive with fossil fuel sources like coal and gas. The trade-off from the renewables is largely their intermittent supply, which requires some form of energy storage in the grid in order to accommodate. That storage requires communication between all facets of a grid, from the generation right the way through to the home via smart meters, in order to efficiently route and store the electricity. At every level, the grid infrastructure is gradually being connected to online platforms, with an envisioned end-goal of reaching eve-ry electricity customer. This is where distributed generation, such as rooftop solar, needs to be combined with in-home storage, or where grid-scale stor-age is paired with those home batteries or charging EVs. At high-er levels, these platforms become the places where a utility gains insight into its generation capacity, so that it can more efficiently purchase energy from wholesalers supplying the baseline loads from non-renewable sources. Such a complex ecosystem would benefit from standardized pro-cesses, at least at the higher layers of the stack. This is where SEPA hopes to come in, acting as a gatekeeper of sorts – easing the integration of disparate systems and approaches, as well as potentially ironing out some of the differences between the utili-ties and the DER providers. SEPA’s current board includes utilities like Southern California Electric, PSE&G, and Duke, as well as equipment suppliers like Siemens and ABB, and regulators and local authorities, with a smattering of consulting types too. SGIP’s board is smaller, but includes Intel, ABB, GE, Entergy, Southern Company, NIST, IEEE, NRECA, EnerNex, CMG, NARUC, and ERCOT.

Utilities and en-ergy suppliers are currently in the middle of a significant transi-tion period, as re-newable energy like solar and wind have be-come cost com-petitive with fos-sil fuel sources like coal and gas.

20 13 April 2017 Riot Issue 154

Riot: tracking disruptive technology and its impact in industry Riot is published by: Rethink Technology Research Ltd, Unit G5, Bristol & Exeter House, Lower Station Approach, Temple Meads, Bristol, BS1 6QS Tel: +44 (0) 117 925 7019 Website: www.rethinkresearch.biz Riot’s main contributors Editor and Senior Analyst: Alex Davies alex@rethinkresearch.biz Analyst: Thomas Flanagan tommy@rethinkresearch.biz Energy Analyst: Jack Vernon jack@rethinkresearch.biz Rethink leadership CEO: Peter White peter@rethinkresearch.biz Research Director: Caroline Gabriel caroline@rethinkresearch.biz About Rethink Rethink is a thought leader in quadruple play and emerging wireless and IoT technologies. It offers consulting, advisory services, research papers, plus three weekly research services; Wireless Watch which has become a major influence among leading wireless operators and equipment makers and Faultline, which tracks disruption in the video ecosystem, which has become required reading for anyone operating in and around quad and triple play services and digital media. Riot is Rethink’s latest research service. Sales contact details John Constant +44 (0)1794 521 411 Email: john@rethinkresearch.biz Simon Thompson +44 (0) 1280 820 560 Email: simon@rethinkresearch.biz