Efficiency gains from machine to machine networking could reduce CO2 emissions by 7.2 Gigatonnes (Gt) by 2020, according to a new report by the Carbon War Room.
An example of Machine to Machine communication is texting your TV box to record a programme. This could be extended so you could tell your boiler to turn off the central heating.
Increasing the number of networked devices that can talk to each other and be operated and adjusted via the internet will underpin the development of the smart grid with potential saving of 2Gt by 2020 from that sector alone, according to the Machine to Machine Technologies research.
Despite the large potential gains from the technology, there are still several barriers holding up adoption of M2M tech.
The sectors big players now need to tackle if they are to open up an industry worth an estimated $1 trillion, according to the report.
“We’ve seen the great potential in this technology and made aggressive investments to capitalize on that potential,” said John Schulz, Director of Sustainability at AT&T, who funded the report.
“We pursued this work with Carbon War Room to tap into their expertise to understand the relationship between this revenue opportunity and potential environmental benefits. This study looks into ways that we can scale that expected huge adoption curve to achieve the benefits faster.”
The latest UNEP Emissions gap report estimates that global greenhouse gas output needs to fall to 44Gt a year by 2020 to limit warming to the 2°C that scientists have recommended as a relatively safe limit. In 2010 this figure was 50.1Gt and headed for 58Gt without series changes to policy.
In order to ensure as wide as possible implementation of M2M technology it needs to be uniform so all the machines are effectively talking the same language.
Other opportunities to control the heating and cooling of buildings, improving the efficiency of supply chains, making sure planes and ships take the shortest smartest route and monitoring agriculture to reduce water and fertiliser use and even to tag cattle so those from ranches that have cleared forests are clearly labelled.
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