Abstract: A method for sharing and analyzing information to support execution of multi-party workflows in an electrification ecosystem. The method may include creating or updating shared data schema and data governance rules associated with data to be received from a plurality of parties, wherein the plurality of parties are stakeholders to the multi-party workflows, and the data is associated with a battery system; submitting the shared data schema and the data governance rules for approval to the plurality of parties; creating or updating decision logics associated with the data to be received; submitting the decision logics for approval to the plurality of parties; receiving the data from the plurality of parties; and applying the approved shared data schema, the approved data governance rules, and the approved decision logics to the multi-party workflows and the received data from the plurality of parties to perform automated decision optimization.

Abstract: A method for demand estimation. The method may include collecting people flow data from a network of a plurality of sensors within an area of interest, wherein each sensor of the plurality of sensors is associated with a user device; processing the people flow data to generate movement trajectories; mapping the movement trajectories to existing transportation network; aggregating the movement trajectories associated with the network of the plurality of sensors to estimate movement flow density; for the people flow data representing less than entire population of the area of interest, performing data simulation to rescale the movement flow density; classifying the people flow data into different transportation types; and generating flow-demand matching by matching current demand with transportation resource information.

Abstract: A method for a system. The method may include receiving information regarding a plurality of nodes of the transportation network, a map associated with the transportation network, and a current demand associated with multiple nodes in the transportation network. The method may further include generating, based on the received information, a demand grid related to the transportation network. The method may also include determining a set of service zones based on the received information and the generated demand grid. The method may further include generating, based on the received information and the set of service zones, a model for route optimization. The method may also include determining, based on the model, at least one candidate path for a vehicle associated with the on-demand transportation service.

Abstract: A method for sharing and analyzing information to support execution of multi-party workflows in an electrification ecosystem. The method may include creating or updating shared data schema and data governance rules associated with data to be received from a plurality of parties, wherein the plurality of parties are stakeholders to the multi-party workflows, and the data is associated with a battery system; submitting the shared data schema and the data governance rules for approval to the plurality of parties; creating or updating decision logics associated with the data to be received; submitting the decision logics for approval to the plurality of parties; receiving the data from the plurality of parties; and applying the approved shared data schema, the approved data governance rules, and the approved decision logics to the multi-party workflows and the received data from the plurality of parties to perform automated decision optimization.

Abstract: A method for a system. The method may include receiving information regarding a plurality of nodes of the transportation network, a map associated with the transportation network, and a current demand associated with multiple nodes in the transportation network. The method may further include generating, based on the received information, a demand grid related to the transportation network. The method may also include determining a set of service zones based on the received information and the generated demand grid. The method may further include generating, based on the received information and the set of service zones, a model for route optimization. The method may also include determining, based on the model, at least one candidate path for a vehicle associated with the on-demand transportation service.

Abstract: An apparatus for providing recommended solutions for a multi-mode transportation problem associated with a multi-mode transportation network. The apparatus may include a memory and at least one processor coupled to the memory. The at least one processor may be configured to receive transportation-related data regarding a plurality of different modes of transportation. The apparatus may further be configured to generate a single-mode data set for each of the plurality of different modes of transportation. The apparatus may also be configured to generate problem-specific harmonized data for the multi-mode transportation network from the received transportation-related data. The apparatus may further be configured to provide a set of recommended solutions for the multi-mode transportation problem based on the problem-specific harmonized data.

Abstract: The invention provides seamless journey experience for passenger in multimodal mobility travel using a single ticket for different trip sections and when multimodal operators provide passenger proof-of-transit, smart contracts enable automated fare disambiguation among them. The single truth of passenger travel journey on single ticket in multimodal mobility helps to also develop incentivizations/rewards for passengers, and incentivize modal operator's based on service level agreements in a consortium.

Abstract: Systems and methods described herein can involve establishing a blockchain network between a plurality of organizations, each organization representing a different mode of transport and/or transit oriented service providers; deriving multi-modal features from first data sources of the plurality of organizations in the blockchain and second data sources off the blockchain; constructing a multi-modal network that integrates the different mode of transports from the plurality of organizations from the derived multi-modal features; executing smart contracts between the plurality of organizations across the blockchain in accordance with service level agreements generated from reinforcement learning through the multi-modal model derived from the multi-modal network; and providing, through a micro-application, access to multi-modal transportation services based on the executed smart contracts.

Abstract: Presenting data in a scalable format includes obtaining input from multiple sensors, grouping a subset of the multiple sensors based on similar parameter values, and allocating a section of a display screen to the subset based on a number of the multiple sensors in the subset.

Abstract: Presenting information from multiple sensors includes obtaining data points from multiple sensors in a geophysical survey, analyzing the data points to create multiple presentations derived from the data points about said geophysical survey, and switching from displaying one of the multiple presentations to another of the multiple presentations as commanded with user input.

Abstract: Presenting data in a scalable format includes obtaining input from multiple sensors, grouping a subset of the multiple sensors based on similar parameter values, and allocating a section of a display screen to the subset based on a number of the multiple sensors in the subset.

Abstract: A method for processing data streams comprises receiving a multiplexed data stream from a number of sources, the sources comprising a number of sensors and a number of vibroseis trucks to stimulate an environment in which the sensors are deployed, processing the data stream using a number of operators, with the operators, utilizing a number of compute resources to process the data stream, and with a data flow graph and scheduler module, scaling the number of compute resources used to process the data stream.