The location of mobile workforces can also be tracked via smartphones or vehicle tracking systems which enables management to better understand how to optimize the use of experts and assets across a geographic area.
Today wireless remote sensors are capable of bi-directional data exchanges. Sensors can both send data to the central server and receive data in the form of machine commands. In many cases remote sensors can receive commands from central servers to adjust settings or perform other functions via wireless data exchanges. This opens up a wide area of possibilities. Today we see irrigation canal gates, greenhouses and other facilities and assets controlled remotely using this technology.
M2M is a way of connecting physical and digital things to each other wirelessly through a network. These connections, and the data exchanged, can provide real time visibility and access to information about the physical world and the environments around the M2M enabled objects in it. This is an important component used to develop full situational awareness of a given area of operations. Used in the context of an electrical grid, enterprise asset management system, plant maintenance, field service automation system, or any other mobile workforce management solution, this data can lead to innovations and gains in efficiency and productivity that were never before possible.
Juniper Research predicted that the number of M2M and embedded mobile devices will rise to approximately 412 million globally by 2014. ABI Research used a more conservative set of numbers and says that there were approximately 71 million cumulative M2M connections in 2009 and predicts this will rise to about 225 million by 2014. GSMA predicted that there will be over 50 billion embedded mobile devices by 2025. All of these predictions represent big numbers and a lot of data. The challenge for managers today is how to turn this high volume of available data into actionable intelligence.
Some of the key markets for M2M systems are:
- Utilities/Smart grids
- Fleet management/Automotive systems
- Equipment monitoring/Plant maintenance
- Connected homes/Home Energy Management Systems (HEMS)
- Healthcare - Remote patient and health monitoring, medical equipment monitoring
- Remote asset management monitoring
- Security systems
- Consumer electronics (eReaders, Wireless Printers, Appliances, etc.)
In a world filled with M2M data feeds, the question is what can you do with all of this data? Where can this data provide value? This is where business intelligence applications are needed - solutions that have the capacity to immediately analyze vast amounts of data and recommend how best to use it for optimal operational efficiencies.
I am seeing companies like ClickSoftware embed artificial intelligence into their scheduling and workforce optimization and field services solutions. They use collected data to predict the needs of the field services workers. M2M data enhances these kind of solutions with additional data provided by sensors on machines, in plants and across utility grids. ClickSoftware has a new software component titled ClickButler designed to predict, based on a wide range of collected data, the information most relevant and needed by your mobile field services teams. This is just the beginning of a new wave of innovation.