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Category: Big Data

Will IoT improve your eating habits?

Will IoT improve your eating habits?

29720_french_fries_inline_640_8“This extra-virgin olive oil is a fake!”

I recently came across an interesting article by Amy Webb on how Internet of X will change our lives as we know them now. Essentially, Webb’s theory is that soon, we’ll be able to analyze any product we consume or use – ranging from the chicken in our meal to the multi-vitamin we take – thereby giving us enough information to make informed choices.

The technology for doing most of it exists today – the sensors, spectrometers and gateways, in addition to big data and advanced analytics tools needed. However, someone has to securely store the massive amount of data that can potentially generated, and host advanced search technologies to query the data – question is, who will be paying for that?

Some of it can be paid for by product companies – an example Webb provides is researching the seasoning on your french fries at the restaurant to buy the seasoning to use at home. The seasoning manufacturer would be happy to provide the information in order to grow their sales – but that may not cover the expenses for hosting, access and security.

This brings to mind what we (I work for Harman Connected Services) are doing with a large agricultural company, as well as a different foray into precision farming with a large telecom company.

foodIn the first instance, from a crop grower technology perspective, we are working with measuring the NPK (Nitrogen, Phospate, Potassium) levels – which is one of the biggest focus area of nutrition management of crops.

Nutrition Management broadly addresses 3 areas:

  1. For the grower the cost of nutrition – Optimizing the spend on fertilizer, ensuring that just the needed amount of nutrition is purchased and applied.
  2. For the grower ensuring the the crop gets the required amount of nutrition. The need varies based on growth stage of the crop as well as external factors such as temperature, humidity, soil quality etc.
  3. From the regulatory authority perspective ensuring that seepage of nitrate from fields into neighboring lands (could be an organic field etc.) or water bodies is minimal.

The technologies used are available today – IoT sensors, big data, analytics – but stretching that to Webb’s example is easy. If the data of the food source data (similar to what is collected by us above) was made available by the grower, you could potentially see where your spinach was grown, and how much fertilizer was used to grow it. You could also see if there were any sustainable agriculture practices followed…the list goes on…

All this is very exciting, and businesses will eventually find a way to monetize the data so that it can be made available to the general public securely…just don’t carry a fake Gucci bag to your next cocktail party!

Marx, Monetization and M2M – where do we go from here?

Marx, Monetization and M2M – where do we go from here?

sharingA recent article in The Economist caught my eye – firstly because the tag line referred to digitization being a threat to the industrial leadership of Europe’s largest economy, and secondly because it brought to mind Karl Marx’s words from over 150 years ago.

The article, Does Deutschland do digital?” talks about how German manufacturing companies, long focused on engineering and precision, are now trying to transform themselves (slowly) into data and software companies. The trend is nothing new – here in the States, we have been seeing provocative headlines like “Domino’s Becomes A Tech Company That Happens To Make Pizza” for years. The premise is companies are using the latest advances in mobile, cloud, big data and analytics to improve their business models – and get more revenue from improved services.

marxSo what is so different in the Deutschland? Enter Karl Marx, who in Das Kapital talks about commodities being the fundamental units of capitalism. Commodities, according to Marx have two values – a “use value” – what it does in the way of satisfying needs and wants – and an “exchange value” – the relative value of the commodity in relation to another commodity.

The article talks about a German company founded in 1923 called Trumpf – who is now trying to re-establish itself as a software provider – “Trumpf’s roots in metalworking and other hardware stand in stark contrast to what it is trying to achieve next: building a new business purely based on software and data. Unveiled last month, its online offering, called Axoom, connects machines built by Trumpf and others, and uses the data it collects from them to help customers organise their production—for instance, to warn them when they are running out of material or to order it directly from the supplier. Much like smartphones, Axoom will be able to run “apps” from other providers, such as software to schedule workloads, or to predict when machines will need a spare part”.

But here, we are talking about information as a commodity which has an “exchange value”. When would sharing information between apps become a “loss of sovereignty”?

“Apple and Google are pressing carmakers to install the operating systems they have designed for cars’ entertainment systems, which in practice will suck up all sorts of other data about the car and its occupants. Carmakers are realising that to give up this territory would risk their “sovereignty over the data” generated by their vehicles, in the words of Wilko Stark, Daimler’s strategy chief. They could end up like Samsung, whose profits from smartphones are limited by the fact that it depends on Android, Google’s mobile operating system”.

So how do we get past the fear of sharing?

One way is by looking to bureaucracy – the “Open Data Initiative” of several governments has put a lot of data (albeit mostly mundane) in public domain – which can then be used by startups like Zillow to create apps which can monetize the inferences from this data. Other good examples cited in another article in the same issue of The Economist are around corruption – “Making data public can also fight corruption. Last year IMCO, a Mexican think-tank, found over 1,400 teachers apparently born on the same day in 1912, prompting a purge of the “ghosts” from payrolls. British and Nigerian officials have used property and company registers published by several governments to investigate money-laundering…”

The other way could be revenue sharing – where the platform company acts as a trusted broker for the monetized data – providing various participants their proportionate share of the revenue stream or utility. The first step, a la Google or Apple, would be to build the right platform for that industry sub-vertical, where companies would want to share data and use shared data (remember Marx’s “exchange value“?)

Take an example of Navistar – a manufacturer of commercial and defense vehicles, which has not been profitable since 2011, in addition to being sued for violation of the Clean Air act.

They use sensors, big data and analytics today to offer efficiency solutions to their customers: Navistar is analyzing data pulled from OnCommand Connection, a remote diagnostics system the company launched in 2013 to monitor performance of more than 150,000 trucks in Navistar’s fleet, including its own international brand, as well as Freightliner, Kenworth, Peterbilt and Volvo makes. The software builds 20 million records a day, measuring fuel economy, geolocations, idle times and potential failures, and recommends corrective measures. Such visibility enables fleet customers, who can monitor the metrics from smartphones or tablets, to schedule maintenance, reducing unplanned repairs and downtime by as much as 30 percent. For example, rather than changing oil based on time or miles logged, the diagnostics software will alert customers when new oil is required.”

This is exciting – but more exciting is the vision around “platform” of their CIO – “ Navistar will eventually build an online portal that integrates telematics data with additional GPS data and parts inventory information, allowing fleet owners to locate the nearest dealer service location where the necessary part is in stock, as well as service locations that have available technicians and bays. The company is also considering offering an analytics service that would enable smaller fleets to acquire operational data about their without ponying up the cash to build their own systems”.

This is where Navistar could be the trusted partner for partners like parts manufacturers or service locations – sharing revenues from the monetized data for the greater good of all the partners subscribed to the platform, while adding more data from partners to extend the exchange value.

I believe we just scratching the surface of new business models to come. As the Economist article states, “It is impossible to predict where the open-data revolution will lead. In 1983 Ronald Reagan made America’s GPS data open to the world after a Soviet missile brought down a South Korean airliner that had strayed into Soviet airspace. Back then, no one could have guessed that this would, one day, help drivers find their way, singles find love and distraught pet-owners find their runaway companions…”

For more of my musings, please visit RajBhandari.info

 

Help…my IOT device is not working or has been hacked…

Help…my IOT device is not working or has been hacked…

GartnerThat may the most common help desk call you may be hearing about in the near future…

We all know about the projected boom of Internet of Things (IoT) enabled devices and sensors, and how that is altering the business landscape for almost every industry (even though the analyst firm Gartner puts it at “Peak of Inflated Expectations”). Examples I am personally working with range from use of IoT from as simple as asset tracking to “intelligent farming/ranching” to “smart buildings” to smart coolers” to “connected health“. – which leads me to believe that IoT is here to stay…and will create a whole new ecosystem of service providers.

IoT has several well-documented limitations – solving those issues will create the IoT leaders of tomorrow .

As everything, from a lamp post to a cow get embedded with a device or sensor with an IP address, and as we move from IPv4 (with about 23 billion IP addresses) to IPv6 (with trillion+ potential addresses), unique identifiers may not be a problem (yet).

The bigger problems are around security and battery life on the sensors. 

Cattle-WatchFirst, the battery life – idea is to reduce the dependence on a field person to swap batteries in remote locations – the good news is that there are quite a few solutions available today, as well as under test. For example, I recently read about a technology, available today, which can harness WiFi networks for powering IoT sensors – “Freevolt harvests energy from RF frequency waves from radio masts and wireless networks, which bounce around the atmosphere. Everything from 2G to 5G networks and even your home Wi-Fi are all food for Freevolt, turning wasted energy into real power…”. Other examples include using rechargeable Li-Ion batteries in conjunction with solar panels for use in devices like parking meters or creating a mesh network using “smart collars” for cows. 

Another angle to this issue could be to reduce the power needed from a network perspective to the bare minimum – for example, Ericsson recently announced their Power Saving Mode “Power Saving Mode is an Ericsson Evolved Packet Core feature based on 3GPP (Release 12) for both GSM and LTE networks. Ericsson contends the feature is able to dramatically extend IoT device battery life up to ten years or more for common use cases and traffic profiles. The capability is defined for both LTE and GSM technologies and lets devices enter a new deep sleep mode – for hours or even days at a time – and only wake up when needed. ..”. Other advances include Low Power Wide Area Networks (LPWANs) and similar technologies.

As these technologies improve and the costs come down, it will add to the ubiquity of IoT devices and sensors.

ikettle_smart_kettleNow the security aspect – much has been written about the hacked Jeep Cherokee or the “not-so-Smart Kettle” – both these scenarios are real, and of great concern. This problem is compounded by the fact that most legacy industrial machine-to-machine protocols, as well as legacy applications in use today do not account for the sheer number of connections or the security advances of today.

“For years, manufacturers of medical devices depended on the ‘kindness of strangers’ assuming that devices would never be targeted by bad actors,” wrote John Halamka, the Chief Information Officer at Boston’s Beth Israel Deaconess Hospital. “EKG machines, IV pumps, and radiology workstations are all computers, often running un-patched old operating systems, ancient Java virtual machines, and old web servers that no one should currently have deployed in production.”

I was reading an interesting viewpoint by Dr. David Bray, CIO of the FCC. His view is that we could learn from a public health type of scenario to improve security – like a mashup of cyber personal hygiene and cyber epidemiology“If we think of the Internet as a series of digital ecosystems where participants need to assume some responsibility for making sure they’re doing their best to keep their Internet devices clean and secure – the digital equivalent of washing their hands – then we can also imagine the need for cyber epidemiology when individual hygiene is insufficient in preventing a mass ‘outbreak’ or individual infection,”

Such a public health scenario may help to a certain extent, but the good news is that there is a bevy of startups tacking this problem from a hardware perspective. An example is a PowerGuard device being developed by a startup called Virta Labs“The PowerGuard device is limited to monitoring and could not block an infection. However, using it could greatly narrow the window of opportunity that an attacker would have to establish a foothold in a sensitive environment subsequent to compromising a device…The devices would also help spot changes in a device’s operation that may be unrelated to malicious activity, helping hospitals, manufacturing firms and the like identify hardware that is in need of servicing…”

To add to all this, there are the new crop of monitoring and services companies, waiting in the wings for the mass deployment…

So whether Gartner places IoT at “Peak of Inflated Expectations”: or “trough of Disillusionment”, I am bullish on the future with IoT and the ecosystem around it…

Marty McFly was right – Flying Cars are here…

Marty McFly was right – Flying Cars are here…

back-future-part-ii_3Well, sort of…

Thirty years after “Back to the Future Part II”, it is amazing to see that some of the predictions the movie made in the 80s are real today – including 3D, abundance of flat screen TVs and drones…but no flying cars yet…

However, the transportation industry is undergoing paradigm shifts in every facet – from supply chain to marketing to to sales to predicting driver behavior and using technology to improve it.

Much has been written about using IoT, big data and analytics throughout the supply chain to improve the productivity, logistics, forecasting and predict machine failure. Not surprisingly, it is the emerging area of Connected Vehicles – from Connected Cars to Connected Trucks to Connected Rail – which is igniting possibilities from an end-user, commerce and fleet management viewpoints.

Think about what GPS data, real-time road conditions, weather data, driver behavior history, combined with data from the sensors in the vehicle can do…plus newer technologies like vehicle connected infotainment and dynamic route mapping… Add to that the projection that half the new vehicles shipping by 2032will have robotic autonomous (driver less) capabilities – we are painting a future which obsoletes all the current norms around transportation and commerce.

connected carA lot of this technology is available today – and some of it is under testing. An interesting report talks about “multi-modal mobility” as the future – “With mounting traffic congestion increasingly resulting in lost time and economic value as well as environmental issues, especially in mega cities in developing regions, the focus of both public and private companies in the automotive and transportation industries is shifting to multimodal / intermodal transportation solutions. Traveler information systems providing real-time public transport timetable information, multimodal journey planners, and smartphone-based pedestrian guidance applications are geared at facilitating knowledge of and seamless access to a wide range of mobility solutions. This is prompting even car OEMs such as BMW and Ford to offer solutions beyond the narrow context of the vehicle itself, realizing their products will become part of an integrated intermodal system, offering a balanced range of mobility modes…”

The basic technologies remain the same, but are being continuously improved – automated data collection (via IoT or other data streams), storing the immense volume and variety of data in efficient stores (big data), advanced predictive modeling on this data, and presenting it in the right context and format back to the user.

And just in time for the October 21, 2015 date famously referenced in the movie, learn how a couple of companies – HortonwWorks and Harman (disclosure: I work for Harman) are taking connected cars to the next level at this webinar on Oct 22nd.

 

Precision Farming, or Can a Cow be a Sensor?

Precision Farming, or Can a Cow be a Sensor?

riverOver the weekend, I had a chance to read an excellent book called “A River Runs Again”, by Meera Subramanian. Written in the “sandals on the ground” journalistic style, Subramanian uses fluid prose to document her travels across India and her interviews with various people and entities.

However, this is not just another book, listing the environmental and social issues faced by a developing country. The difference in this book, which is divided into sections based on the Five Elements–  air, earth, water, fire, and ether – is the real life stories of positive change being brought about by organizations and individuals – from conversion back to organic farming to creating a vulture aviary to bring back the Parsi Sky Burial ecosystem…

Though not explicitly stated, these change agents are using technology as a growth enabler – which brings us to “smart farming”. There has been quite a bit of work done around ” smart farming” or “precision agriculture“. The Food and Agriculture Organization of the UN (FAO) predicts that the global population will increase to 9.6 billion people by 2050 – and 70% more food needs to be produced to feed that population. Precision agriculture tries to use existing technology like GPS, sensors, big data, IoT and analytics to optimize the crop yields. Even the farm animals play a part, with embedded IoT sensors to reduce the carbon footprint. It does not imply automated farming by machines, but helping the farmer’s gut instinct with intelligent decisioning.

Graphic_Japanese_Farming_v5-01As the author of a report on smart farming states, “I would like to highlight the fact that the aim should not be ‘industrializing’ agriculture, but make agriculture more efficient, sustainable and of high quality. We should not look for revolutions. We should look for re-interpretation of the farming practices through use of data-centric technologies. And this re-interpretation should be placed also within a new vision of rural areas.”

There was another article recently which talks about venture funding for companies using advanced data collection and analytics in agriculture. A good example they give is that of a machine, which can “visually characterize each plant through real-time image capture and processing, use algorithms to determine which portions of the plant to keep and precisely eliminate the portions of the plants that are unwanted.

Their Zea product enables high-throughput, field-based phenotyping. Using computer vision, Zea counts plants, measures plant spacing, builds canopy height distributions and measures key physiological parameters — all based on imagery. In our minds, this is machine learning at its finest…”

The demand is there, and technology is available now. The piece which is missing is to make the technology accessible and affordable for those who need it the most…

 

Google, others take on human trafficking using big data tools

Google, others take on human trafficking using big data tools

 

Google, others take on human trafficking using big data tools.

Data analysis, image recognition and mapping programs are helping anti-trafficking nonprofits not only locate victims in real time, but predict their victimizers’ next moves. Going into 2014, the companies and their partners are exploring how to share information to develop global prevention strategies based on traffickers’ behaviors.

Palantir’s software, which sifts volumes of unrelated data for meaningful connections, is key to many of those efforts, including speedy response to victims who call hotlines. It instantly pulls information from disparate sources such as license plate numbers, online ads and cellphone records to locate trafficking victims and connect them with help.