International Business Machines Corporation

Fabio Latuf Gandour

Ricardo Luis Ohta

Alecio Pedro Delazari Binotto

Ademir Ferreira Da Silva

Marcelo Nery Dos Santos

Ademir Fereira Silva

Vinicius Costa Villas Boas Segura

Leonardo Guerreiro Azevedo

Alecio Binotto

Sensor data is detected from at least one sensor selected and installed for detecting operating conditions of at least one equipment. The sensor data includes an operating condition of at least one equipment. The sensor is selected dependent on indications of a user restriction and a predictive model. A sensor data signal is generated dependent on the sensor data. The sensor data signal is transmitted to a network device for collecting the sensor data and transforming the collected sensor data into a formatted transmission signal having a format for transmission over a network to a network server. The network server receives the formatted transmission signal for performing on-demand service of at least one of analysis, reporting and visualization dependent on the operating condition.

On-demand remote predictive monitoring for industrial equipment analysis and cost forecast

In response to receiving an input of a user criteria for operating a system, one or more predictive models are selected in dependence on the user criteria. The predictive models predict behavior of the system and are stored in the memory with one or more system performance models that control operation of the system. The selected performance model(s) is implemented to select a subset of sensors that monitor physical conditions of the system and/or environmental parameters thereof, and is also used to select one or more of the system performance models that conform to the user criteria. One or more actuators associated with the system are controlled according to inputs received from the selected subset of sensors and the selected performance model(s). The same concepts are valid for other areas rather than maintenance, like optimization in the area of the internet of things, dynamic system reconfiguration, preventive healthcare.

Dynamic and reconfigurable system management

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Sao Paulo, Brazil

Fabio Latuf Gandour