Abstract: An example method may include receiving, via a graphical user interface, credentials for connecting to a data store containing a plurality of datasets and connecting to the data store using the credentials. A selection of a target metric to predict using the machine learning model can be received, via the graphical user interface, and datasets included in the plurality of datasets that correlate to the target metric can be identified by analyzing the datasets to identify an association between the target metric and data contained within the datasets. The datasets can be input to the machine learning model to train the machine learning model to generate predictions of the target metric, and the machine learning model can be deployed to computing resources in a service provider environment to generate predictions associated with the target metric.

Abstract: A technology is described for automating deployment of a machine learning model. An example method may include receiving, via a graphical user interface, credentials for connecting to a data store containing a plurality of datasets and connecting to the data store using the credentials. A selection of a target metric to predict using the machine learning model can be received, via the graphical user interface, and datasets included in the plurality of datasets that correlate to the target metric can be identified by analyzing the datasets to identify an association between the target metric and data contained within the datasets. The datasets can be input to the machine learning model to train the machine learning model to generate predictions of the target metric, and the machine learning model can be deployed to computing resources in a service provider environment to generate predictions associated with the target metric.

Abstract: A hydraulic cartridge valve including a housing with an interior, first and second ports that pass through the housing, a poppet in the housing interior, and an activation sensor. The poppet moves between a closed position that blocks flow through the housing interior between the first and second ports, and an open position that allows flow through the housing interior between the first and second ports. The activation sensor senses poppet position, and generate a valve open signal when the poppet is in the open position. The activation sensor can be a contact or contactless sensor, and can be located in an opening through the housing blocked by a diaphragm. A pushrod pushed by the poppet can activate the sensor, such that when the poppet blocks flow the pushrod is separated from the diaphragm, and when the poppet allows flow the pushrod is pushed towards the diaphragm.

Abstract: A hydraulic cartridge valve including a housing with an interior, first and second ports that pass through the housing, a poppet in the housing interior, and an activation sensor. The poppet moves between a closed position that blocks flow through the housing interior between the first and second ports, and an open position that allows flow through the housing interior between the first and second ports. The activation sensor senses poppet position, and generate a valve open signal when the poppet is in the open position. The activation sensor can be a contact or contactless sensor, and can be located in an opening through the housing blocked by a diaphragm. A pushrod pushed by the poppet can activate the sensor, such that when the poppet blocks flow the pushrod is separated from the diaphragm, and when the poppet allows flow the pushrod is pushed towards the diaphragm.

Abstract: A technology is described for automating deployment of a machine learning model. An example method may include receiving, via a graphical user interface, credentials for connecting to a data store containing a plurality of datasets and connecting to the data store using the credentials. A selection of a target metric to predict using the machine learning model can be received, via the graphical user interface, and datasets included in the plurality of datasets that correlate to the target metric can be identified by analyzing the datasets to identify an association between the target metric and data contained within the datasets. The datasets can be input to the machine learning model to train the machine learning model to generate predictions of the target metric, and the machine learning model can be deployed to computing resources in a service provider environment to generate predictions associated with the target metric.

Abstract: A fluid analyzing system includes a handheld device and a management system. The handheld device includes a fluid analysis control module and a telematics device. The fluid analysis control module is configured for initiating acquisition of a sample of a fluid and providing the sample to a microfluidic analyzer for conduction of a microfluidic analysis. The telematics device is coupled with the fluid analysis control module and configured with a wireless transceiver. The management system is located remotely from the telematics device, and configured for wirelessly receiving results of the microfluidic analysis transmitted from the telematics device.

Abstract: A fluid analyzing system comprises a telematics device, a fluid analysis control module, and a locomotive management system. The telematics device is coupled with a locomotive. The fluid analysis control module is coupled with the locomotive and the telematics device. The fluid analysis control module is configured for initiating acquisition of a sample of a fluid of the locomotive and providing the sample to a microfluidic analyzer for conduction of a microfluidic analysis in response to occurrence of an analysis trigger. The analysis trigger comprises an operating characteristic of the locomotive. The locomotive management system is located remotely from the locomotive and the telematics device. The locomotive management system is configured for wirelessly receiving results of the microfluidic analysis transmitted from the telematics device.

Abstract: A fluid analyzing system comprises an electronic control module and a telematics device. The electronic control module is coupled with an asset. The electronic control module is configured for initiating acquisition of a sample of a fluid of the asset and initiating a microfluidic analysis of the sample in response to occurrence of an analysis trigger. The analysis trigger comprises an operating characteristic of the asset. The telematics device coupled is coupled with both the asset and the electronic control module. The telematics device is configured for wirelessly transmitting results of the microfluidic analysis to an asset management system located remotely from the asset and the telematics device.

Abstract: An electrohydraulic controller feedback system and method including an electrohydraulic operator controller and a feedback mechanism is disclosed. An operator controls a machine hydraulic function using the electrohydraulic operator controller, the feedback system senses a property of the hydraulic function, and generates tactile feedback in the electrohydraulic operator controller based on the sensed property. The electrohydraulic operator controller can be, for example, a joystick or control lever. The tactile feedback can be vibrations that vary based on the sensed property. The vibration can vary according to a profile relating the vibration amount to the sensed property. The profile can include portions of various shapes, for example, linear, exponential or parabolic, and can include breakpoints. The profile can include high sensitivity regions where small changes in the sensed property result in large vibration changes.

Abstract: An electrohydraulic controller feedback system and method including an electrohydraulic operator controller and a feedback mechanism is disclosed. An operator controls a machine hydraulic function using the electrohydraulic operator controller, the feedback system senses a property of the hydraulic function, and generates tactile feedback in the electrohydraulic operator controller based on the sensed property. The electrohydraulic operator controller can be, for example, a joystick or control lever. The tactile feedback can be vibrations that vary based on the sensed property. The vibration can vary according to a profile relating the vibration amount to the sensed property. The profile can include portions of various shapes, for example, linear, exponential or parabolic, and can include breakpoints. The profile can include high sensitivity regions where small changes in the sensed property result in large vibration changes.

Abstract: A fluid analyzing system comprises an electronic control module and a telematics device. The electronic control module is coupled with an asset. The electronic control module is configured for initiating acquisition of a sample of a fluid of the asset and initiating a microfluidic analysis of the sample in response to occurrence of an analysis trigger. The analysis trigger comprises an operating characteristic of the asset. The telematics device coupled is coupled with both the asset and the electronic control module. The telematics device is configured for wirelessly transmitting results of the microfluidic analysis to an asset management system located remotely from the asset and the telematics device.

Abstract: A fluid analyzing system comprises a handheld device and a management system. The handheld device includes a fluid analysis control module and a telematics device. The fluid analysis control module is configured for initiating acquisition of a sample of a fluid and providing the sample to a microfluidic analyzer for conduction of a microfluidic analysis. The telematics device is coupled with the fluid analysis control module and configured with a wireless transceiver. The management system is located remotely from the telematics device, and configured for wirelessly receiving results of the microfluidic analysis transmitted from the telematics device.

Abstract: Novel solutions to the challenges of obtaining accurate information about a user's or an organization's carbon footprint. In some cases, these solutions can obtain and/provide feedback about a user's carbon output based on the user's habits and choices. Some solutions are designed to supply services to individuals as well as commercial ventures and for a variety of vehicle fleets, including without limitation construction equipment. In different aspects, systems in accordance with various embodiments enable a variety of types of users to create their own carbon emission generation profile based on vehicle type; track, estimate, and store their emissions in a database; analyze their results and performance, using established methods and metrics and/or automatically update all operating parameters of interest.

Abstract: A differential pressure sensor (10) has a sensor die (16) attached to a stress isolation package base (12) with a bonding glass (27) having a similar coefficient of thermal expansion. The bonding glass, and alternately an aluminum layer, provides a hermetic seal between the stress isolation base and sensor die. Pressure is applied to the sensor die port (24). A plastic housing (14) is attached to the stress isolation base with an adhesive (29). A port (23) in the plastic housing is filled with a silicone gel (22). A second pressure source is transferred by way of the silicone gel to the sensor die. Any hostile chemical entering the via contacts the first surface of the sensor die to assert pressure against a transducer circuit (25) to generate the electrical signals representative of the applied pressure but are isolated from the sensitive interconnects by the hermetic seal.

Abstract: A dual absolute pressure sensor independently converts first and second external pressures to first and second electrical signals respectively. A package body has first and second openings for receiving the first and second external pressures to outside surfaces of first and second sensor die attached to opposite surfaces of an internal glass substrate that separates the first and second openings. The first sensor die includes a first cavity having a reference pressure to measure against the first external pressure and develop a first differential pressure. A first piezoelectric network converts the first differential pressure to the first electrical signal representative of that pressure. The second sensor die includes a second cavity having a reference pressure to independently measure against the second external pressure and develop a second differential pressure. A second piezoelectric network converts the second differential pressure to the second electrical signal representative of that pressure.