We have described in a recent article the dimensions of the M2M Switch currently taking place in the wireless industry: a renewed emphasis on machine-to-machine communications away from human-to-human communications, and the implementation of a new business model based on new “ABCs”: low Average Revenue per Unit or ARPU; low bandwidth or data rate transfer; and low churn or customer attrition. These characteristics are fundamentally different from the wireless operator’s traditional business model. However, the shift in the business model foundation is not the only radical change. In addition to bringing a new focus, the M2M Switch transforms the way businesses operate. As millions of remote devices are going to be linked up together, the ability to better comprehend and monitor the operational quilt or the business environment in general will be increased, and, as a result, overall productivity enhanced. The M2M Switch infuses new life into the business-to-business (B2B) M2M market.
Expressions such as “Smart Grid” (promoted by many governments), “Smart Device” (e.g., U.S. Telecommunications Industry Association), “Smart Service” (Qualcomm), “Smarter Planet” (IBM), “Connected Work” (Deutsche Telekom) or “Smart+Connected Communities” (Cisco), all reflect in their own way the transformation of M2M into an agent of improved efficiency and cost effectiveness. The UK wireless giant Vodafone, in a 2010 comprehensive White Paper on “Global Machine to Machine Communication,” echoes this permeating role within the same historical context in which we introduced the M2M Switch: “Over the next few years, M2M could be a key enabler in helping to restore confidence after the world economic crisis, providing the next leap forward in global productivity in much the same way as the mobile phone did in the latter part of the century.”
Intelligence is not added by the operator in a reactive mode; rather, it is an inherent component of the technology. It is no longer enough to learn that the inventory of a vending machine is low, a waste disposal container is getting full or a pipeline has too much corrosion; corrective actions must be triggered by the machine (sensor, etc.) to other machines, seamlessly and immediately. Note that for the time being, this corrective action could consist in the dispatch of a person while the next wave will be closing the loop to automatically trigger remediating events.
A 2007 article in Annals of Emergency Medicine called “Replacing Hindsight With Insight: Towards Better Understanding of Diagnostic Failures” (Vol. 49, No. 2, February 2007) underlines the flawed diagnostic model for physicians who are “presumed to react to some state of the world, rather than anticipating some possible future state and acting to facilitate or forestall it.” Likewise, in the M2M world, especially in the business-to-business market, customers are looking for more than data collection; they want their M2M partner to make sense of the “real-world context” and provide services that meet or exceed the end users’ expectations through better information management. As M2M systems are getting more sophisticated, and software-based systems leaning on the processing power of Cloud Computing are spreading rapidly, customers want not only to learn “what has happened” (hindsight) but also “why it happened” (insight) in order to optimize their own solutions. Enabling real-time business intelligence, which is a combination of M2M technology and business analytics, is also a consequence of the M2M Switch.
Insight can be obtained at two different levels. Intelligence can be supplied on the given solution that is being utilized by the end user (e.g., energy consumption) (level 1), but it can also be infused along the M2M value chain (level 2). We call “M2M’s intelligent edge” the bridge between the M2M “factory” and the M2M customer where the sensing device, the network and application interact and morph into a single interface. For instance, regarding the smart grid, the meters, the connection gear (wireless network and gateway) and the application software can be monitored to ensure optimum operation (level 2), in addition to providing valuable detailed information on the energy consumption (level 1). In the healthcare arena, for example, critical data on a heart condition and/or other ailment can be sent to physicians and other medical personnel who remotely monitor the patient (level 1), and, at the same time, feedback data on the intelligent edge can be made available to the M2M provider to monitor and control the efficiency of the components of the M2M solution (level 2).
It is worth noting that M2M standardization, which is now well underway in many Standards Developing Organizations (SDOs) around the world, will facilitate the management of the intelligent edge in promoting interoperability.
As M2M evolves from a data collector to an information producer and transforms hindsight into useful insight, it also shifts its emphasis from hardware to software. At the same time, the seamless integration of M2M data to a customer’s management information system (ERP, CRM, etc.) requires that they be transmitted safely and securely. As a result, M2M is now on its way to become an inherent component of companies’ “data nervous system.”