One of the biggest technological advances today is machine-to-machine (M2M) technology, and M2M networks have impacted our lives, work and the way business is conducted. These radio-frequency identification technology networks have virtually revolutionized supply chains, upgraded health information systems to real-time analytic applications and improved information on infrastructure in areas of energy and security.
M2M projects can be found in a vast number of fields: architecture, construction, engineering, communications, cellular, medical and environmental. Many businesses are finding success with the use of M2m technology,. For example, Qualcomm, using M2M, launched a medical-grade cloud server that links personal health and fitness monitoring devices to medical professionals and, when appropriate, directly to consumers.
To many experts and professors these are only the first steps toward the Internet of Things (IoT)—a network joining of billions of devices, such as, robots on factory floors, microprocessor coffeemakers in kitchens, and Internet connections.
“Despite rapidly multiplying examples of M2M communication at work, realizing the promise of the IoT will require much more time and research. Reaping the benefits of large-scale, machine-to-machine communications is orders of magnitude more complicated than the deployments that exist today,"says Brian Proffitt, adjunct professor in the University of Notre Dame's Mendoza College of Business.
Therefore, universities research centers, along with the National Institute of Standards and Technology, Institute of Electrical and Electronics Engineers (IEEE (News - Alert)), and others have been pushing to standardize M2M protocols to form a common language to help build API’s.
M2M networks are challenged by a lack of common protocols, says Stephen Miles, a research scientist at the Massachusetts Institute of Technology's Auto-ID Labs, where the phrase "Internet of Things" was coined a decade ago. The real-time analytics, along with the APIs that deliver data from sensors and other devices, are closely held, as are applications that manage the flood of data created by M2M networks. When an organization purchases a new network-connected device, it does not expect to purchase entirely new network management systems for each device, Miles says.
In pursuit of this goal, Purdue University (News - Alert) has created a model that identifies the components that need to interface in an M2M network, called HARMS—humans, software agents, robots, machines and sensors.
"Purdue is developing its own API for the HARMS infrastructure, but building it for all the machines out there would take more time than we have left in the world," stated Eric Matson, assistant professor-researcher for Purdue’s M2M Lab "New devices come out every day. New infrastructure comes out every day. When you look at how devices consume meaning, content and context and their semantics, the problem becomes even more complex."
Growing recognition of the promise of M2M networks will ensure the continuation and spread of university research on related topics, and demand for related classes already is increasing, Proffitt says.
M2M is a growing field, curricula and research centers devoted to M2M are available in many universities.
Edited by Rich Steeves