Machine to Machine Analytics

Enterprise Machine–to–Machine (M2M) projects have replaced many legacy processes to serve basic operational needs, e.g. food ordering to kitchen dishes preparation to utility smarts meters or connected coffee vending machines. These projects are embedding, connectivity, instrumentation and intelligence in core business processes and assets. M2M analytics will utilize the new data streams and capabilities of the systems to enable business transformation and usher a new wave of innovation.

Ericsson forecasts 50 billion connected devices worldwide by 2020, Berg Insight forecasts 290 million connected mobile devices in the US by 2015 and IMS Research forecasts 100 million connected devices per year reflecting 30% CAGR through 2015. This growth in M2M data should ultimately provide enterprises with more real-time, valuable insights.

Forecasts for connected M2M devices vary based on research house and definitional inclusions, but high subscriber growth is certain.

M2M data sources like machine logs, biometric sensors and video surveillance generate significant volumes of data that necessitate the use of Big Data technologies to store and process. Web giants like Google and Facebook served as the early pioneers of big data analytics.

An example of competitive vendor analysis could be as below,

Be it operational optimization, new sales models, decision or product innovation Infion is holding hands with its clients and partner organisations to take them through the journey of machine to machine analytics.