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Dynamic Placement of Wireless Power Recharge Router based on Power Requirements Disclosure Number: IPCOM000239527D
Publication Date: 2014-Nov-13
Document File: 3 page(s) / 66K

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The Prior Art Database


Disclosed are a method and system to use analytics and predictive analysis to create the perfect distribution of energy amongst power supply stations in remote areas in order to keep all sites energized. The method uses analytics to determine the perfect timing (i.e. the time to start charging and the period for which the charge is to take place) in order to create the optimal distribution of power among these stations, and fulfill the energy requirement in a novel way.

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Dynamic Placement of Wireless Power Recharge Router based on Power Requirements

Powerful wireless devices use magnetic resonance to increase power transmission speed and quality. This capability can be used to provide analytics to perfectly distribute the energy to multiple stations.

Examples of environments that have great potential to benefit from wireless power transmission include:

 Remote areas with rugged terrain that do not have traditional wired power transmission

 Disaster areas that need rapid deployment of distributed power stations

 Special outdoor events covering wide area

The example used throughout this disclosure is that of a remote rescue scenario such as one that can occur during a raging wildfire. This disclosed method applies to many types of rescues including storms, injured mountain climbers, etc. The capability described herein is useful in additional scenarios.

Rescue workers and rescue teams tend to be separated by distances, and power needs to eventually get to all of these places. A mechanism is needed by which to make available a wireless power recharge point, allowing the rescue team to continue to work without any shortage of power. Some means are in place, and the described method significantly adds to current capability.

At a typical rescue site, multiple different devices are used that need power. This includes heavy rescue machinery, lighting equipment, mobile phones, and many devices in between. Often, a shortage of battery power tends to hamper work.

The novel contribution provides a method for optimal use of a limited power supply by calculating the most efficient distribution to all stations involved based on usage, predictive future usage, capability to hold a charge, known power amounts, and comparison against other stations. The method enables wireless distribution of power with optimal placement of wireless power stations.

This solution includes a system that charges one station for the exact right amount of time (not necessarily to full charge) based on calculable qualities such that ALL stations are kept at peak capability. At peak, these stations are charged as much as humanly possible without harming other sites that might also need to tap into this very limited power supply. The method and system prioritize the power requirement points. This calculation is based on available power in the devices, number of available/participating devices, consumption rate, etc. Additionally, the combination of all stations allows the system to more accurately portray the needs of one station versus another.

The method and system begin by analyzing the dynamic power requirements for all of the different power areas in the site. In the given example, these are different stations


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within a larger rescue site. The different station...