Kurzweil's predictions about how the world will change

Thanks to Rainer von Ammon, I came across a blog post that brings Ray Kurzweil's predictions for the future.   Some highlights:

In 2017 we'll have self driving cars

In 2020 we'll print our designer clothes at home

In 2033 we'll get all of our energy from the sun

In 2040 those who us who will be still alive will stay young forever (Kurzweil's ultimate goals).

Some of us may be able to watch whether all these predictions come true... 

Summary of 2013 as reflected in this Blog

2013 is phasing out and this is a time to do a short summary via this Blog.

This year I have been abroad   times:  Two of them were vacation  - long one in New Zealand  (pictures on FaceBook) and very short one in Paris.  I have also  been twice in the USA (January and July), and attended DEBS 2013 in Arlington, Texas.   once in Luxembourg (for negotiation of 2 EU projects), once in Brussels (as reviewer for another EU project), once in Barcelona (for the ACM multimedia conference), and once in Hong Kong (for ER 2013).

The main activity in 2013 was around the event model, I explained some of the background early in the year, presented it first in ER 2013, and towards the end of the year we also produced YouTube  video clip.

We achieved a great progress in this front, and will see which shape and direction it will take. 

The most read post on this Blog this year was the post on comparison between S4 and Storm.  Some other well read posts were: causality vs. correlation  Web serviced triggered by SAP ESP,  Is Philosophy dead?  (an "off topic" post, but I have an academic degree in Philosophy in my record...). and "Event Model - what comes first, the logic model or data model?"

What is coming for me in 2014?  --   stay tuned!

One more thing:   This year I 'gained' a Wikipedia entry about me  (some revisions are needed, but according to Wikipedia rules, I am not allowed to update it)..  

Happy New Year. 

58 sensor applications

I came across a site that lists "top 50 sensor applications for the smarter world".  It actually list 58 applications partitioned to the following areas::  smart cities, smart environment, smart water, smart metering, security & emergencies, retail, logistics, industrial control, smart agriculture, smart animal farming, domestic & home automation, and eHealth.  

I worth digging into the different areas to check the potential applications, and the role of event processing in each of them. 

On reversing the roles - the kid got it!

Earlier this week I spent 2 hours with a group of high school students that were selected to be part of the "President of Israel program to discover and cultivate the inventors and scientists of the future".   The IBM Haifa Research Lab took part in this program, by conducting a sequence of sessions, each with one of   our local scientists (I was the last in the sequence).  

It was a very interactive session, and as part of it I described four scenarios of event processing in different areas (typical examples I am using in my talks:  the car theft example, the intensive care unit scenario, the never-lost luggage scenario, and the cold chain scenario that we use in our recent TEM video clip.  
I have asked them what they think is the common denominator among all these scenarios -- they said many right things, but one kid said the most important thing:   "in these scenarios the roles are reversed, instead of the usual way that the person tells a computer what to do, here the computer tells a person what to do".
This kid will  definitely have a bright future... 

Gartner's recent predictions about business intelligence and analytics

A recent set of predictions by Gartner, state that Business Intelligence and Analytics will remain top focus for CIOs through 2017. 

It mentions two interesting observations:   One is that the confusion in the market about the term "big data" and its tangible results constrain the spending and limit the growth of BI and analytics software.   The second observation is that By 2017, more than 50 percent of analytics implementations will make use of event data streams generated from instrumented instrumented machines, applications and/or individuals.  

This is consistent with the Gartner's term -  "two tier analytics",  where event processing is the second tier, after historical data analytics.  While the need to consolidate analytics and event processing is becoming more pervasive, the utilization barrier and the need to battle complexity is still a common denominator. 

The Event Model: short promo on YouTube

Following the first exposure of "The Event Model" in ER 2013,  we have produced a 5 minutes video clip explaining shortly the idea.  The screenwriters were Fabiana Fournier and Sarit Arcushin and the video was produced by Tammy Dekel, Hanan Singer and Chani Sacharen (who is also the narrator). 

The video clip issues a call for partnership in investigating this model -  either by working with us on use cases to validate the model, or working with us on the challenges in further developing the model.

On Rolls Royce's engine health management

In DEBS 2013, Roger Barga from Microsoft mentioned in his keynote talk that Rolls Royce is proposing to its customers a model of engine hours as a service, and used it as an example that event processing can be enabler of changing business models.    I recently talked with somebody about these type of systems and decided to follow up and learn more about the Rolls Royce system using the available information on its website.   The service is enabled by "Engine Health Management" (EHM)  The illustration above shows some of the engine sensors.   The monitoring follows the scheme: Sense-Acquire-Transfer-Analyze-Act.

The sense phase deals with the activation and capture of the sensors.

The acquire phase stands for a combination of routing reports in various milestones (takeoff, climb, summary at landing)  and detection of abnormal situations (this is the "derive" part of event processing).

The transfer phase deals with the communication to the ground operation  center

The Analyze phase is a manual phase that take the input from the previous phases and adds manual control and decision about next actions 

The Act phase deals with the actions required -- such as servicing and part replacement and determine the urgency and location.

This is consistent with the 4D (Detect-Derive-Decide-Do) model.  Here the decision is mainly manual.  It seems that this is one of the early cases where the use of sensors and event-driven applications are used to employ new business models.   More on business models change  -- later.