“Capital-C” convergence starts by combining data streams in real time. These data streams can emanate from any or all of the following sources: Hybrid PDAs and personal communicators; RFID; GPS transceivers; Digital video; etc., etc.
Next (and herein lies the real power of capital-C convergence) these data streams are co-mingled — often in real time — to yield new types of information and new IT applications. Here are some examples:
Healthcare Delivery
Convergence is becoming increasingly evident in healthcare settings. In the operating room, for example, Partners Healthcare in Boston converges RFID streams with hospital data to enhance the outcome of patient hospitalization.
At the heart of its new operating room facility is RFID data capture in the form of plastic ID bracelets for patients and a variety of RFID tags placed on medical devices and medications.
As a patient is wheeled into the O.R., the hospital’s IT system identifies the patient via RFID and locks onto the patient’s electronic records. It will also identify the scheduled procedures for that O.R. session, what hospital equipment and medications are needed, and can verify that only the proper items and medications are in the room.
If, in an emergency, a piece of equipment is needed from elsewhere in the hospital, the system uses RFID to immediately identify the nearest source.
Beyond the O.R., RFID usage is expanding to other areas. Whenever a medicine is dispensed in a hospital setting, the hospital’s internal system scans RFID tags on medication containers to verify that it is in fact the prescribed medication for that patient.
The convergence of multiple RFID data sources with stored hospital data in real time greatly reduces the number of preventable mistakes (further yielding a reduction in insurance premiums), shortens patient in-hospital time, and yields higher utilization of the O.R., the staff, and equipment.
Down on the Farm
Multiple data streams from farm equipment with WiFi-enabled, equipment-mounted GPS sensing devices, can be converged with weather satellite data to increase crop yields.
For example, manual tractor operation can result in nonparallel tracking, which means that either sections of the field are missed or overfilled (leading to measurable wasted time).
GPS-controlled tracking can eliminate these conditions and allow farm machinery to be operated at night. Next, add data collecting harvesters that can measure the amount of harvested grain and its moisture content and transmit that data wirelessly back to a centralized system. Finally, stir-in satellite imagery, topographical data, and thermal data.
The result is information that can be correlated and used for high-efficiency seeding, fertilizing and irrigation. Essentially, every square inch of farm land can be treated uniquely, managed by systems communicating through wireless networks with automated farm equipment.
The Home
The home environment is really the next capital-C convergence frontier. It’s where RFID, GPS, digital video, WiFi, enhanced PDAs, and myriad sensing devices all can play a role together.
Consider the lowly toaster. Give Bluetooth connectivity to your heating, ventilation, and air-conditioning (HVAC) system via your home network and it will adjust itself by exploiting collected humidity data — perhaps to cook longer in higher humidity, thus providing a more consistent “toast” experience.
If you live in a climate that experiences winter, consider your furnace (perhaps you’d rather not). Start with a programmable thermostat that communicates with your home network. Add an embedded processor that stores historical data such as operating statistics, weather data, and home environmental data.
Finally, give the furnace a Web interface so that you can build value-add programs and Web views to monitor, control, and automate the operation of your furnace over a range of weather conditions. Think of the possibilities for optimum performance.
If you’re wondering what sort of magic glue there is out there that binds these data sources together, I can start with two. XML comes to mind immediately and is well-known. However, StreamSQL is another lesser known and more frontier-ish converger of data streams, and one that was built for real time information-yielding applications. Google “StreamSQL” to get started.
Capital-C convergence is a seamless crossing of boundaries, sharing and converging information with other information sources, hopefully without delays or gaps. It’s the art of combining that will produce new information sources and new user-facing applications. Converge and create.
John Webster is senior analyst and founder of Data Mobility Group . He has held the positions of director of Computing Research with Yankee Group’s Management Strategies Planning Service, and senior analyst with International Data Corp. He is also the co-author of “Inescapable Data – Harnessing the Power of Convergence” (Prentice Hall, 2005).