Predicting and correcting vegetation state

    公开(公告)号:GB2602929A

    公开(公告)日:2022-07-20

    申请号:GB202205196

    申请日:2020-09-24

    Applicant: IBM

    Abstract: Methods and systems for managing vegetation include training a machine learning model based on an image of a training data region before a weather event, an image of the training data region after the weather event, and information regarding the weather event. A risk score is generated for a second region using the trained machine learning model based on an image of the second region and predicted weather information for the second region. The risk score is determined to indicate high-risk vegetation in the second region. A corrective action is performed to reduce the risk of vegetation in the second region.

    Reconfigurable gas sensor architecture with a high sensitivity at low temperatures

    公开(公告)号:GB2541525A

    公开(公告)日:2017-02-22

    申请号:GB201611888

    申请日:2016-07-08

    Applicant: IBM

    Abstract: A gas sensing device 10 comprises a dielectric substrate 16, a heater 18 integrated into the substrate, an insulating dielectric 12 formed over the heater, a gas sensing layer 14, contacts 26 formed on the sensing layer, and a noble material 24 formed on a portion of the sensing layer between the contacts to act as an ionising catalyst such that upon heating to a temperature adsorption of a specific gas changes electronic properties of the sensing layer to permit detection of the gas. The device may have a plurality of different noble metals 24 to sense different gases. A calibration system includes a gas sensing device mounted on a substrate, a gas canister for storing a calibration gas and an injector for enabling local gas release for calibrating the sensor.

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