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. rarSaving the Big Picture in Multi-Sensor Technologies

The development of multisensor technologies has received much attention lately. These technologies use multiple sensor methods for the same analysis problem, and also use this information from different sensors to improve decision-making. For instance, the use of X-ray detectors in airport security and passenger identity card check systems, as well as the use of different sensors to detect whether a package is intact, hazardous, or infected, has shown significant improvements in the efficiency of these systems. However, much less attention has been paid to the big picture.

What is the big picture? Simply put, it is the overall operational goal of any technology; what is the desired future state of the world, or the state of the world that we want to achieve? Saving lives is the big picture in healthcare, protecting the environment is the big picture in urban planning, etc. In a similar way, the big picture in multi-sensor systems is the desired future state of the world, or the state of the world that we want to achieve. As a simple example, consider a fire alarm that employs different sensors for different purposes. These sensors can include heat-sensing systems and light-sensing systems. Each sensor can capture its own information and feed it to a decision-making system that determines whether there is a fire or not. The multi-sensor system can tell us whether a fire has started or not. However, the big picture is not only a mechanism to report a fire. A more complete picture of the fire is needed in order to determine the extent of the fire or the type of damage.

In theory, the decision-making system can inform the firefighters and other first responders about the fire and if there are any victims. However, in the real-world examples, such as hospitals, fire departments, police, hospitals, and other regulatory bodies, there are still considerable obstacles that need to be overcome to achieve this picture. This can include lack of a protocol to define how to collaborate, lack of an interoperable communication network that integrates different methods, lack of a protocol for integrating the data from different sensors, lack of a set of methods to combine the data collected from different sensor types, and lack of data that is close to the desired picture.

Towards this big picture, there have been several recent advances in multi-sensor systems. These include the integration of different sensor methods (different cameras or different X-rays) and a sensor-selection

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