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IT Equipment Acclimation Analytics Using Big Data From Interactive Maps, Weather Forecasts, and Actual Weather Conditions

IP.com Disclosure Number: IPCOM000246387D
Publication Date: 2016-Jun-02
Document File: 4 page(s) / 75K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a method to determine acclimation time for equipment without using sensors, but rather weather data and shipping route data. The data is collected prior to shipping such that the best shipping route, corresponding to the least amount of acclimation time, is chosen. The prediction model can be updated real-time based on the current weather conditions when enroute.

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IT Equipment Acclimation Analytics Using Big Data From Interactive Maps , , Forecasts, ,

and Actual Weather Conditions

and Actual Weather Conditions

Disclosed is a method to determine acclimation time for equipment without using sensors, but rather weather data and shipping route data. The data is collected prior to shipping such that the best shipping route, corresponding to the least amount of acclimation time, is chosen. The prediction model can be updated real-time based on the current weather conditions when enroute.

    Transportation of information technology (IT) equipment in non-temperature controlled trucks can result in exposure to freezing (below 0 degrees C, 32 degrees F) temperatures during the winter months. The climate throughout the journey from manufacturing location to final destination plays a role in the amount of acclimation time that is needed to prevent condensation. It is the transition from the cold outdoor shipping environment to the warm indoor staging or installation environment that can lead to condensation and even frost. Powering on IT equipment with condensation present can create shorts and damage the system. The disclosed method predicts an amount of acclimation time needed for a particular delivery based on shipping route and weather forecasts. The predictions may be validated based on real-time weather data.

    In an example embodiment, the disclosed method allows for the prediction of acclimation time using the cloud for a given piece of IT equipment (thermal mass) based on transportation route and weather forecasts. The acclimation time can be built into the overall delivery schedule so that condensation is prevented and the hardware installers can do their job immediately upon arrival, thereby eliminating multiple trips to a data center. The predictive analytics can also determine the best route which would require the least amount of acclimation time. Although the

journey may be longer, the overall sum of the trip plus the acclimation time is shorter. Even shipping days could be selected such that the package is shipped prior to or after a weather front that reduces or even eliminates acclimate time.

    The method may also use a GPS positioning while enroute to get real-time weather conditions and adjust the initial forecast as well as acclimation time estimate. The GPS can be part of a mobile phone or the truck's navigation system. The method uses cloud data, analytical methods, and case-dependent factors to determine the acclimation time rather than on-board measurements as these devices would require a power source (e.g., battery, capacitor).

    Figure 1 depicts a flow of the disclosed method where a point-to-point shipping route can be mapped out with approximate hourly locations identified using receiving and/or shipping scan data taken by all carriers for receipt, delivery, and cross-docking products, and information about the shipment (service level, carrier, etc.). At each location, the forecas...