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1.
公开(公告)号:US20230177966A1
公开(公告)日:2023-06-08
申请号:US17808262
申请日:2022-06-22
Applicant: Honeywell International Inc.
Inventor: Kirupakar JANAKIRAMAN , Kalimulla KHAN , Todd MATHIS , Ramkumar RAJENDRAN , Srihari JAYATHIRTHA , Subhransu SAHOO
CPC classification number: G08G5/003 , G08G5/006 , G08G5/0008 , G07C5/006
Abstract: Disclosed are methods and systems for bi-directional communication between one or more vehicles and a cloud based computing system. For instance, a method may include processing, by a first digital twin of the cloud based computing system, a first request received from and/or sent to a gateway unit associated with a first vehicle, the request comprising data related to one or more vehicle operations; validating, by an avionics data processing service (ADPS) in communication with the gateway unit, the first request against an operational parameter corresponding to the one or more vehicle operations; upon validating the first request, matching, by the ADPS, the operational parameter with a flight operation; and upon matching the operational parameter with the flight operation, inserting, by the ADPS, a modified flight operation into the flight management system of the vehicle.
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2.
公开(公告)号:US20210288887A1
公开(公告)日:2021-09-16
申请号:US17334414
申请日:2021-05-28
Applicant: Honeywell International Inc.
Inventor: Ramchandra JOSHI , Kirupakar JANAKIRAMAN , Narayanan SRINIVASAN , GaneshKumar NAGARAJ , Karthick SENGODAN , Nilesh DESAI
Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for a contextual transformation of an analytical model for an industrial internet of things (IIoT) edge node. For instance, the method may include receiving the analytical model from a cloud service; obtaining local data of the IIoT edge node; analyzing the local data to determine a situational context of the IIoT edge node; determining whether to transform the analytical model based on a fit between the analytical model and the situational context; and in response to determining to transform the analytical model, transforming the analytical model based on the situational context to derive a transformed analytical model.
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3.
公开(公告)号:US20200084113A1
公开(公告)日:2020-03-12
申请号:US16128236
申请日:2018-09-11
Applicant: Honeywell International Inc.
Inventor: Ramchandra JOSHI , Kirupakar JANAKIRAMAN , Narayanan SRINIVASAN , GaneshKumar NAGARAJ , Karthick SENGODAN , Nilesh DESAI
Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for a contextual transformation of an analytical model for an industrial internet of things (IIoT) edge node. For instance, the method may include receiving the analytical model from a cloud service; obtaining local data of the IIoT edge node; analyzing the local data to determine a situational context of the IIoT edge node; determining whether to transform the analytical model based on a fit between the analytical model and the situational context; and in response to determining to transform the analytical model, transforming the analytical model based on the situational context to derive a transformed analytical model.
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公开(公告)号:US20200301760A1
公开(公告)日:2020-09-24
申请号:US16358422
申请日:2019-03-19
Applicant: HONEYWELL INTERNATIONAL INC.
Inventor: Kirupakar JANAKIRAMAN , Rajeev MOHAN , Nayyar Azam Khan RAO , Ramkumar RAJENDRAN
IPC: G06F9/54 , G06F16/903 , G06F16/901 , G06Q50/30
Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for providing application programming interface (API) mashups. For instance, the method may include hosting a plurality of certified FMS micro-services associated with a plurality of FMS APIs; hosting an API mashup generator to perform an API mashup process and an API mashup recommendation process, the API mashup process generating combinations of APIs that include one or more APIs from the plurality of FMS APIs, other avionics APIs, and/or third party APIs; and hosting a service mesh to process a user request from a user device for the API mashup recommendation process or an invoke micro-service process.
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公开(公告)号:US20200285571A1
公开(公告)日:2020-09-10
申请号:US16804970
申请日:2020-02-28
Applicant: HONEYWELL INTERNATIONAL INC.
Inventor: Rajeev MOHAN , Ramkumar RAJENDRAN , Kirupakar JANAKIRAMAN
IPC: G06F11/36
Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for fault injection and ensuring failsafe FMS SaaS platforms. For instance, the method may include observing a behavior of a platform; building a hypothesis about a steady state behavior based on the observing the behavior of the platform; determining whether a request for fault injection has been received; in response to receiving the request for the fault injection, performing the fault injection; observing a response of the platform to the fault injection; determining whether the fault injection is at an end; and in response to determining that the fault injection is at the end, collect and analyze data of observed response(s).
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公开(公告)号:US20200226940A1
公开(公告)日:2020-07-16
申请号:US16245589
申请日:2019-01-11
Applicant: Honeywell International Inc.
Inventor: Narayanan SRINIVASAN , Rajeev MOHAN , Kirupakar JANAKIRAMAN , Nayyar Azam Khan RAO , Ramkumar RAJENDRAN
Abstract: Disclosed are systems, methods, and non-transitory computer-readable medium for providing one or more flight management system (FMS) services as a Software as a Service (SaaS) with context-aware intelligence for a plurality of FMS users. For example, a system may include a context analyzer system configured to determine based on one or more context analysis parameters, a prediction engine configured to determine prediction data based on the one or more contexts and/or one or more prediction parameters, a recommender engine configured to determine recommendations based on one or more recommendation requests and/or one or more prediction data, a background processing system configured to identify background operations to support an operation of a first FMS service and generate background support data for the first FMS service, and a message bus in communication with an API gateway, the context analyzer system, the prediction engine, the recommender engine, and the background processing system.
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公开(公告)号:US20240177618A1
公开(公告)日:2024-05-30
申请号:US18158151
申请日:2023-01-23
Applicant: Honeywell International Inc.
Inventor: Kalimulla KHAN , Kirupakar JANAKIRAMAN , Raghu SHAMASUNDAR
CPC classification number: G08G5/0039 , B64D45/00 , B64D2045/0075
Abstract: A system includes avionics line-replaceable units (LRUs); a mission manager including application programming interfaces (API); a processing device; and a memory storing one or more machine readable instructions causing the system to: communicatively couple the mission manager to external avionics services via a data gateway to receive updated mission conditions at the mission manager; register one of the avionics LRUs with one of the mission manager APIs; receive, at the mission manager, updated mission conditions from the external avionics services via the data gateway; provide one or more of the one or more updated mission conditions to the registered avionics LRU based on one or more of an updated mission plan and an unexpected update to the mission condition; and control one or more aircraft systems based on one or more of the updated mission plan and the unexpected update to the mission condition.
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公开(公告)号:US20220166635A1
公开(公告)日:2022-05-26
申请号:US17246161
申请日:2021-04-30
Applicant: Honeywell International Inc.
Inventor: Rajeev MOHAN , Kirupakar JANAKIRAMAN
Abstract: Disclosed are methods, systems, and computer-readable medium for context-specific granular access to flight management system (FMS) SaaS using adaptive IAM. For instance, the method may include receiving, at one of a plurality of application programing interface (API) endpoints of a flight management system (FMS) software as a service (SaaS), a request from a client; determining whether the request is authorized; in response to determining the request is authorized, analyzing the request to determine a context of the request and determine whether the request includes an intent; transmitting a message to a particular functionality of the FMS SaaS based on the context and the intent; determining whether the client is associated with a subscription type; filtering a data stream from the FMS SaaS in accordance with the subscription type and the context; generating a response based on the filtered data stream; and transmitting the response to the client.
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公开(公告)号:US20210194767A1
公开(公告)日:2021-06-24
申请号:US17173620
申请日:2021-02-11
Applicant: Honeywell International Inc.
Inventor: Ramchandra JOSHI , Kirupakar JANAKIRAMAN , Ganeshkumar NAGARAJ , Narayanan SRINIVASAN , Karthick SENGODAN , Jim DARROCH
IPC: H04L12/24 , G05B23/02 , H04L29/08 , G05B19/418
Abstract: Computer-implemented methods for configuring an Industrial Internet of Things (IIoT) edge node in an IIoT network to perform one or more functions, comprising: performing a situation analysis to determine a required change in one or more of an analytical model, a runtime component, and a functional block of the IIoT edge node based on a change in the one or more functions; and automatically provisioning a new or updated functional module to the IIoT edge node, based on the situation analysis, the new or updated functional module including one or more components, wherein each component includes at least one of a rules set, a complex domain expression with respect to a process industry, an analytical model, and a protocol decoder.
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10.
公开(公告)号:US20200285996A1
公开(公告)日:2020-09-10
申请号:US16805101
申请日:2020-02-28
Applicant: Honeywell International Inc.
Inventor: Kirupakar JANAKIRAMAN , Rajeev MOHAN , Ramkumar RAJENDRAN
Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for cognitive services for a FMS SaaS platform. For instance, the method may include obtaining training data; training reinforcement learning model(s) using the obtained training data; in response to receiving a request for cognitive services from a user device, analyzing a query of the request for cognitive services using at least one reinforcement learning model of the trained reinforcement learning model(s); determining intent, entity(s), emotion, and/or context of the query based on an output of the at least one reinforcement learning model to form a cognitive services request; applying a second at least one reinforcement learning model of the trained reinforcement learning model(s) to the cognitive services request to determine one or more services to invoke; and transmitting a result to the user device based on an output of the one of more invoked services.
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