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IBM and Libelium Launch Internet of Things Starter Kit

IBM and Libelium, a wireless sensor network hardware provider, today released an Internet of Things Starter Kit to enable dozens of sensor applications ranging from monitoring parking spaces or air pollution to providing assistance for the elderly.

Created by IBM scientists and Libelium engineers to ease application development, testing, and scalability of wireless sensor networks (WSN), the new Internet of Things Starter Kit integrates Libelium’s Waspmote wireless sensor platform with IBM’s Mote Runner software and 6LoWPAN, which allows every single sensor and device to connect directly to the Internet using the new IPv6 protocol.

IBM Mote Runner is an open software development platform that connects sensor and actuator motes within wireless sensor networks based on the IETF 6LoWPAN protocol specification. With the new Internet of Things Starter Kit, a real-time operating system is integrated in Libelium Waspmote nodes to support more that 60 different sensors available “off the shelf,” allowing developers to easily build any application on top. The Internet of Things SDK also includes the source code of the 6LoWPAN libraries so that researchers can modify and add their own algorithms and improvements.

“We have worked closely with IBM to offer a development platform that can be used for both simulation and real IPv6 sensor connectivity,” said David Gascón, CTO at Libelium. “This platform is a powerful tool for improving and testing 6LoWPAN capabilities in the context of wireless sensor networks and the Internet of Things.”

“If we can harvest the Big Data insights from all of the things connected to the Internet we can more precisely understand how our world actually works,” said Thorsten Kramp, a computer scientist at IBM Research. “By making Internet of Things application development easier, the answers to the grand challenges of our age becomes more feasible.”

The Waspmote Mote Runner Developer Kit is available today at here.

Meet Node-RED, an IBM project that fulfills the internet of things’ missing link

node-red-screenshotFrom GigaOm:

If you play around with enough connected devices or hang out with enough people thinking about what it means to have 200 connected gizmos in your home, eventually you get to a pretty big elephant in the room: How the heck are you going to connect all this stuff? To a hub? To the internet? To each other?

It’s one thing to set a program to automate your lights/thermostat/whatever to go to a specific setting when you hit a button/lock your door/exit your home’s Wi-Fi network, but it’s quite another to have a truly intuitive and contextual experience in a connected home if you have to manually program it using IFTTT or a series of apps. Imagine if instead of popping a couple Hue Light Bulbs into your bedroom lamp, you bought home 30 or 40 for your entire home. That’s a lot of adding and setting preferences.

If you take this out of the residential setting and into a factory or office it’s magnified and even more daunting because of a variety of potential administrative tasks and permissions required. Luckily, there are several people thinking about this problem. Mike Kuniavsky, a principal in the innovation services group at PARC, first introduced me to this concept back in February and will likely touch on this in a few weeks at our Mobilize conference next month. He likens it to a more organic way of programming.

The basic idea is to program the internet of things much like you play a Sims-style video game — you set things up to perform in a way you think will work and then see what happens. Instead of programming an action, you’re programming behaviors and trends in a device or class of devices. Then you put them together, give them a direction and they figure out how to get there.

Over at IBM, a few engineers are actually building something that might be helpful in implementing such systems. It’s called node-RED and it’s a way to interject a layer of behaviors for devices using a visual interface. It’s built on top of node.js and is available over on github.

The idea behind the node-RED effort came from playing around with connected devices, and the work it took to make things work together. The engineers behind the code — Nicholas O’Leary, Dave Conway-Jones and Andy Stanford-Clark — are also working with IBM’s MQTT messaging protocol. But with node-RED they aren’t focused on how devices talk to each other, but how they work together.

“The first version of node-RED was all about MQTT and how can we move messages between different topics and do it in a really lightweight way,” said O’Leary. But eventually it became more about a way to tell devices what you’d like them to do as opposed to having to tell each of them how to do it added Conway-Jones.

More info here.

How Can IBM’s Approach To Sensors Change The World?

Around the world, the increased use of sensors — and the data insights they provide — is leading to better management of resources and increased efficiency. A recent article on Forbes.com highlights how IBM is creating smarter cities with sensor technology. The article also discusses how advanced application of sensors can be used to address any number of everyday urban challenges from finding a parking space to increasing access to critical information in the wake of a natural disaster.

Unfortunately, the widespread use of sensors can still be cost-prohibitive. Few organizations can afford to spend hundreds or thousands of dollars per sensor and companies need to be working hard on the idea of bringing the cost down to an affordable level. The key is to make it easier and cheaper for everyone to gain access to the sensor space.

Besides cost, there are two other barriers hampering the widespread adoption of sensors. The first is that much of the sensor industry is focused on the sensor base or the sensors themselves rather than combining all the components to present a complete solution. In many cases the end user or system integrator must put together different components, write the software and then embed it with the sensor hardware.

The second area of focus for many vendors is the big push for cloud-based data collection systems. However, many of these are generic APIs that work with any platform that is configured to use them.  By themselves they are good ways to visualize your data, but not in the context of any real analysis or domain-specific expertise.

The reality is the end user needs both preconfigured hardware and cloud-based monitoring combined to serve a specific purpose. Users want sensors solutions that are easy to install and setup with clear instructions that explain what they’re capable of doing. They also need sensors that are easy to connect to other software and can integrate seamlessly with sensors from multiple vendors.

To be successful, organizations need to provide cheap, easy, and complete solutions that are broad enough to work with other systems. Sensors and the valuable insights they provide could be the key to smarter, more efficient cities and societies. It’s vital to develop integrated systems that are more affordable and readily available.

More info here.

IBM launches an appliance for the ‘Internet of things’

Preparing its customers to join the emerging ’Internet of things’, IBM has released a new appliance built to manage and route a voluminous amount of machine-to-machine small data messages

Using the MQTT (the Message Queuing Telemetry Transport) format, the IBM MessageSight appliance is capable of processing over 13 million messages per second, all of which could arrive from as many as 1 million end-nodes.

“It’s a huge breakthrough in scale,” said Mike Riegel, who is the IBM vice president of mobile and application integration middleware.

The IBM MessageSite was one of a number of new products and updates that the company announced as part of its Impact conference, being held this week in Las Vegas.

IBM designed this appliance, which will be available for customers on May 24, to specifically work with what is being called The Internet of things.

The Internet of things is not a network, but a new buzzphrase describing the growing use of network-connected embedded microprocessors, often connected to sensors or other data-gathering instruments. Because microprocessors are now so inexpensive and networks are so pervasive, such embedded systems could provide a wealth of data that organizations in most industries could use to monitor and improve operations.

For instance, a new car today may have dozens of microprocessors that run millions of lines of code, Riegel said. The car maker could ingest all the data these embedded systems produce, supplying their customers and themselves with pertinent information about how well the vehicle is operating.

By 2020, there might be as many as 22 billion embedded systems and other portable devices connected to the Internet, according to IMS Research. Collectively, these systems may produce more than 2.5 quintillion bytes of new data every day, estimated the IT research company.

More info here.

A Giant Step Forward for the IoT and Big Data

Andy Stanford-Clark, an IBM Master Inventor who lives in the United Kingdom, jokes that his goal was “world domination” in 1999 when he and Arlen Nipper of Eurotech invented a protocol aimed at greatly improving machine-to-machine communications. This was at the time when another British technology pioneer, Kevin Ashton, coined the term “Internet of Things” to describe how the Internet could be connected to the physical world via a vast network of sensors. Sanford-Clark believed that his protocol, now called MQ Telemetry Transport, or MQTT for short, would enable organizations to quickly and affordably gather, integrate and make use of all of that sensor data. It would be an essential underlying technology for the Internet of Things.

Fast forward to today. OASIS, one of the leading technology standards bodies governing the evolution of the Internet, has just announced that it will accept MQTT as an industry standard protocol. This move paves the way for the technology to be used widely for applications ranging from power distribution and public safety to retailing, smart phones and auto communication systems. MQTT now has the potential to have the same kind of impact on the world as HTTP, which is a key part of every Internet address for computers and Web sites. Proponents of the Internet of Things believe there could be up to 50 billion sensors hooked up by the year 2020–turning the promise of Big Data into a reality. “The vision of billions and trillions of connected devices can now come true,” says Stanford-Clark. “The implications are huge. We can solve the energy crisis and improve agriculture, transportation and healthcare. It will make getting things done easier, cheaper and more efficient.”

More info here.

IBM Looks Ahead to a Sensor Revolution and Cognitive Computers

From the NYT:

The year-end prediction lists from technology companies and research firms are — let’s be honest — in good part thinly-disguised marketing pitches. These are the big trends for next year, and — surprise — our products are tailored-made to help you turn those trends into moneymakers.

But I.B.M. has a bit different spin on this year-end ritual. It taps its top researchers worldwide to come up with a list of five technologies likely to advance remarkably over the next five years. The company calls the list, “Five In Five,” with the latest released on Monday. And this year’s nominees are innovations in computing sensors for touch, sight, hearing, taste and smell.

Touch technologies may mean that tomorrow’s smartphones and tablets will be gateways to a tactile world. Haptics feedback techniques, infrared and pressure-sensitive technologies, I.B.M. researchers predict, will enable a user to brush a finger over the screen and feel the simulated touch of a fabric, its texture and weave. The feel of objects can be translated into unique vibration patterns, as if the tactile version of fingerprints or voice patterns. The resulting vibration patterns will simulate a different feel, for example, of fabrics like wool, cotton or silk.

The coming sensor innovations, said Bernard Meyerson, an I.B.M. scientist whose current title is vice president of innovation, are vital ingredients in what is called cognitive computing. The idea is that in the future computers will be increasingly able to sense, adapt and learn, in their way.

That vision, of course, has been around for a long time — a pursuit of artificial intelligence researchers for decades. But there seem to be two reasons that cognitive computing is something I.B.M., and others, are taking seriously these days. The first is that the vision is becoming increasingly possible to achieve, though formidable obstacles remain. I wrote a piece in the Science section last year on I.B.M.’s cognitive computing project.

The other reason is a looming necessity. When I asked Dr. Meyerson why the five-year prediction exercise was a worthwhile use of researchers’ time, he replied that it helped focus thinking. Actually, his initial reply was a techie epigram. “In a nutshell,” he said, “seven nanometers.”

Read the whole article here.

Immediate availability of IBM Mote Runner beta 8 for Windows, Linux, and MacOS.

Mote Runner, IBM’s infrastructure platform for wireless sensor networks (WSN), consists of two parts: a run time for mote-class hardware such as MEMSIC Iris motes, and a development environment for WSN applications.

The Mote Runner on-mote run-time platform is based on a virtual machine tailored from scratch for resource-constraint hardware environments.

For this, it introduces a new byte-code language that, besides being compact and efficient, provides native support for reactive programming by means of delegates. Together with the run-time library built on top, Mote Runner provides a purely event-driven and thread-free programming model.

Blue ZThe development environment of Mote Runner consists a complete tool chain (i.e., converter, assembler, optimizer, shell) to develop mote applications in high-level object-oriented languages such as Java. It comes with its own IDE based on Eclipse as well as a mote and network simulation environment to ease application development and testing. A web-based deployment and monitoring framework in concert with an edge server finally allows the integration and visualization of Mote Runner sensor networks.