Viewpoint: Raising the bar on M2M telematics through predictive analytics

Viewpoint: Raising the bar on M2M telematics through predictive analytics

As machine-to-machine based applications continue to permeate all aspects of everyday life – from smart traffic control to usage-based insurance – the combination of telematics and predictive analytics using real-time Big Data is enabling a new era in M2M technology.

The number of machine-to-machine (M2M) device connections worldwide is expected to grow from 130 million in 2012 to 2.14 billion by 2021, according to Analysys Mason.

It’s, therefore, little wonder that telematics service providers are busy exploring the various opportunities this presents in everything from automotive to public safety to financial services. And as the sector matures, they are increasingly adding real-time predictive analytics to the mix.

Key beneficiaries

Green tech, which includes automotive, is one of the key beneficiaries of this trend. 

For example, an electric vehicle that you drive home and connect to the electric grid will not only figure out your next commute but also consider your grid’s active load usage and non-peak hours in order to auto-tune the recharging schedule, all this while also taking into account any emergency commutes that might be required, based on your personal commute history and personal associations.

Other key applications in the green tech sector include:

• Automated monitoring of heating, ventilation and cooling for smart buildings

• Street lights that operate based on traffic flow

• Predictive maintenance in farms and mining machinery through improved remote monitoring

Key drivers

Regulatory requirements for safety and energy efficiency are often what’s pushing the various sectors to become innovative.

These include government mandates, such as eCall in Europe, which will force all new passenger and light-commercial vehicles by 2015 to adopt a connectivity link for emergency calls.

The reality is that regulations such as eCall will grow globally and further the demand for telematics with regards to emergency calls, but also for remote diagnostics, remote vehicle control, vehicle software upgrades, electronic toll collection, eco-driving, off-board navigation, smart traffic control, usage-based insurance services and condition-based maintenance.

Other factors that are driving increased adoption of M2M include:

• Standardization and adaptation of IPV6  (Internet Protocol version 6) across industries has opened the possibility for billions of uniquely addressable IP devices

• Wide rollout of 3G and LTE networks is providing devices with always-on connectivity and increased bandwidth, enabling M2M segment applications such as remote surveillance, asset tracking and health meters

• Smart application development is creating new opportunities for application developers to build applications for every possible segment, from smart homes to smart appliances

• Innovations in the retail and consumer electronics segments are pushing the boundaries of connectivity with such applications as wireless payments and connected satellite navigation systems

• The electronics and communications industry is rapidly moving toward intelligent, addressable, embeddable devices enabling seamless communications between every device

Starring role for Big Data

It is the combination of telematics with predictive analytics using real-time Big Data that is making many of these innovations possible. 

At Symphony Analytics, we have, for example, begun working with a large near-field communication (NFC) device manufacturer to track consumer packaged goods (CPG) products to detect pilferage and theft.

We have helped a large media company capture viewing patterns of consumers from different media channels to build a cross-media effectiveness platform. And we have created a Big Data blueprint stack for a large smart-meter manufacturer for operational reporting and forecasting of energy consumption.

Additionally, working with a large automobile research association, we’ve helped it discover the patterns in fuel consumption and engine operations for different road conditions.

M2M predictive analytics is still in its infancy, yet many organizations are already putting their Big Data strategies to work in meaningful ways.

Real-time Big Data computation capabilities have opened the flood gates for creating new predictive analytics capabilities within M2M, enabling real-time control and monitoring to help businesses and people operate smarter, safer and more cost-effectively.

Venkat Rajan is SVP and general manager at Symphony Analytics. The article is based on M2M telematics research by Gopalakrishna Palem, senior architect, Symphony Analytics.

For all the latest telematics trends, check out Insurance Telematics USA 2013 on Sept. 4-5 in Chicago, Telematics Brazil & LATAM 2013 on Sept. 11-12 in Sao Paulo, Brazil, Telematics Japan/China 2013 on Oct. 8-10 in Tokyo, Telematics Munich 2013 on Nov. 11-12 in Munich, Germany, Telematics for Fleet Management USA 2013 on Nov. 20-21 in Atlanta, Georgia, and Content and Apps for Automotive USA 2013 on Dec. 11-12 in San Francisco.

For exclusive telematics business analysis and insight, check out TU’s reports: Telematics Connectivity Strategies Report 2013The Automotive HMI Report 2013Insurance Telematics Report 2013 and Fleet & Asset Management Report 2012.

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