When creating and managing an Internet of Things / machine-to-machine deployment, you’ll want to integrate analytics from the start so you can gain the most value from your investment. Gathering data in real-time helps businesses analyze and decide what optimal actions to take.
A new report by ABI Research confirms the growing role of Big Data in machine-to-machine (M2M) communications and the Internet of Things (IoT), with the analysis firm forecasting that integrating, storing, analyzing, and presenting IoT data will reach $5.7 billion in 2015.
The firm says that in the next 5 years, the market will expand to such an extent that in 2020 it is estimated to account for nearly one-third of all big data and analytics revenues.
“About 60% of this year’s revenues come from three key areas: energy management, security management, as well as monitoring and status applications,” Aapo Markkanen, principal analyst at ABI Research, said in a statement. “Within these segments, we can generally find analytic applications that reduce the cost base of asset-intensive operations (condition-based maintenance), automate routine workflows (surveillance), or even enable new business models (usage-based insurance). “
Aeris offers solutions in all of these markets and is laser-focused on Big Data for its M2M/IoT solutions.
Topics: Big Data analytics
As the Internet of Things (IoT) and Machine-to-Machine (M2M) communications connect millions of diverse machines over networks, the goal is to make the combination of those machines greater than the sum of each type and to provide people with greater information and insight as the ecosystem expands.
To achieve this level of interconnectivity, businesses that depend on those machines need them to work reliably, securely, and cost-effectively – without human intervention. That’s where an unexpected technology function comes in to help: crowdsourcing.