Abstract: A data collection device (100) is described which monitors the environmental conditions and the operations of a medical device (10). The data collection device may be arranged to communicate wirelessly via a cloud computing environment with a central computer (210). The central computer compares the reported use data with a preventive maintenance model to predict when or how the medical device will fail. In addition, the central computer may integrate reports from many data collection devices operating in various environments for the purpose of analyzing and improving the predictive maintenance model.

Abstract: A battery having a display indicating an amount of time the battery can be used before needing to be recharged and/or replaced. The amount of time can be displayed in minutes. An end of life indicator indicating whether the battery should be replaced can also be provided on the battery. The battery can determine the amount of time and an end of life indication based on environmental conditions and/or use. The battery can include sensors for measuring and/or monitoring environmental conditions, as well as a global positioning system (GPS) transponder. The battery can also include a communication link for transmitting data to a central location, a specified location and/or a pre-selected location, which data can include the amount of time the battery can be used before needing to be recharged and/or replaced. The battery can be coupled to and configured to power a device.

Abstract: A data collection device (100) is described which monitors the environmental conditions and the operations of a medical device (10). The data collection device may be arranged to communicate wirelessly via a cloud computing environment with a central computer (210). The central computer compares the reported use data with a preventive maintenance model to predict when or how the medical device will fail. In addition, the central computer may integrate reports from many data collection devices operating in various environments for the purpose of analyzing and improving the predictive maintenance model.