176 results about "Fleet management" patented technology

Techniques for host fleet management in a cloud provider network are described. Forecast data including a forecasted demand for virtual machines in each capacity pool of a set of capacity pools is obtained. A mathematical optimizer application is executed to generate a first optimal fleet plan, the mathematical optimizer application having an objective function to minimize a number of new host computer systems to add to the set of host computer systems to satisfy the forecasted demand for each capacity pool, the first optimal fleet plan includes an identification of a set of hardware types and, for each hardware type in the set, a quantity of new host computer systems of the hardware type. A plurality of new host computer systems is deployed, based on the first optimal fleet plan, for a hardware type in the set of hardware types into the set of host computer systems.

A relative positioning method is combined with the known absolute pose of a primary vehicle to provide the absolute position and / or pose of the secondary vehicle wherein the secondary vehicle is only equipped with a non-contact relative positioning system. Thereby allowing for numerous advantages such as fleet management, safe vehicle interactions, and further automation at a fraction of the cost of using a sensor suite commonly required to calculate the absolute pose of the secondary vehicle.

The present disclosure provides methods, systems, and devices for controlling electric vehicle charging across multiple customers and multiple fleets of electric vehicles. These methods, systems, and devices may implement machine learning to determine distinct charging strategies for a plurality of charging depots. Scheduling methods systems, and devices disclosed herein do not require fixed electric vehicle arrival times but may instead update charging strategies in real time based on changes in a state of a system.

A vehicle includes a chassis, a cab, a drum coupled to the chassis and configured to mix a concrete mixture received therein and selectively dispense the concrete mixture, a chute configured to be operable between a raised position and a lowered position such that, when in the lowered position, the chute is configured to receive the concrete mixture from the drum and provide the concrete mixture to a work location, a sensor configured to detect an operational characteristic and provide signals relating to the operational characteristics, and a control system. The control system is configured to receive the signals relating to the operational characteristic from the sensor, determine, based on signals relating to the operational characteristic, when the vehicle entered an operational state, generate a timestamp indicating when the vehicle entered the operational state, provide the timestamp and the operational state to a fleet management system.

An autonomous warehouse robotics system integrates a multi-sensor platform, adaptive payload handling, dynamic task reallocation, advanced navigation, energy management, and comprehensive safety features into one mobile robot chassis. The system utilizes LiDAR, stereo vision, ultrasonic sensors, mmWave radar, thermal cameras, and event cameras to perform complete environmental sensing and obstacle detection. Sensor fusion combines adaptive weighting, multi-modal data integration, and statistical filtering to create high-confidence maps for reactive path planning and collision avoidance. The robot's payload system features machine vision for item recognition, telescopic lifts, variable-width grippers, and real-time toolhead verification to handle a variety of goods. Fleet management is achieved through dynamic task reallocation that considers robot location, battery level, and operational delays, all coordinated by a cross-platform middleware architecture that ensures standardized communication, remote monitoring, and over-the-air updates among diverse robot brands. Energy management optimizes power usage via predictive routing, autonomous return-to-charge, and auction-based scheduling. Safety is maintained through proximity detection, behavior-based intervention, and human-robot cohabitation protocols while advanced localization is enhanced by fusing ultra-wideband positioning with visual landmark alignment, inertial sensing, and machine learning to deliver high accuracy in non-line-of-sight conditions. An onboard edge AI module further refines navigation and task prioritization through neural network inference, ensuring robust, adaptive operation in dynamic, unstructured warehouse environments.

A system includes a fleet resources data store that maintains a fleet resource inventory indicating fleet resources that can be assigned to perform tasks. For each fleet resource, the inventory indicates features of each fleet resource and a respective status. A set of task definitions is accessible to an intelligence layer to facilitate improving task definition based on feedback from task-specific outcomes. The system receives a job request for a robotic fleet to perform a job and determines a job definition data structure indicating a set of tasks to be performed for the job. The system applies an outcome of performing a task by a resource assigned to perform the task to a machine learning system of the intelligence layer that facilitates improving, based on the outcome, the set of task definitions. The system updates the set of task definitions based on a result of applying the machine learning system.

A product delivery system includes a product transport vehicle having at least a plurality of tank compartments, internal valves, control valves, fluid property sensors, temperature sensors, overfill sensors, pressure sensors, a system controller, and a memory module. The product delivery system may be operable to communicatively connect with the loading system at a loading station, a fleet management system, or a cloud system to obtain information, such as the amount of liquid product to be loaded into a tank compartment. The product delivery system may be operable to compare the volumes of the tank compartments with the amounts of liquid product to be loaded at a loading station and maintain the internal valve or control valve in a locked state or transition the internal valve or control valve to an unlocked state based on the comparison. Other comparisons based on liquid type or distribution tank volume can also be made.

The present disclosure generally relates to identification and prioritization of autonomous vehicle (AV) data collection and data offload. In some aspects, the present disclosure provides a process for receiving one or more data collection triggers from an AV fleet management system, wherein the one or more triggers identify at least one condition that triggers collection of AV data by an AV; compiling the AV data in response to detecting the at least one condition identified by the one or more data collection triggers; determining a set of priorities that are associated with the one or more data collection triggers, wherein the set of priorities includes at least one instruction for prioritizing transmission of the AV data to the AV fleet management system; and transmitting, based on the set of priorities, the AV data to the AV fleet management system.

The invention provides a commercial vehicle abnormal energy consumption identification system and method based on Internet of Vehicles multi-dimensional data. The commercial vehicle abnormal energy consumption identification system based on Internet of Vehicles multi-dimensional data comprises a data acquisition module, a data processing module, an abnormal energy consumption identification module, an abnormal energy consumption reason diagnosis module and a pushing module. The commercial vehicle abnormal energy consumption identification method based on the Internet of Vehicles multi-dimensional data comprises the following steps: S1, collecting vehicle data and carrying out preprocessing; s2, abnormal energy consumption identification is carried out based on the vehicle data, and high-energy-consumption vehicles are screened out; s3, diagnosing the cause of high energy consumption; s4, pushing a diagnosis result; according to the method, comprehensive energy consumption analysis is carried out on multi-dimensional data such as vehicle states, driving tracks and driving behaviors, multi-level similarity analysis is carried out on similar vehicles, routes and road characteristics, high-energy-consumption vehicles are recognized more accurately, and errors of a single standard are avoided; abnormal energy consumption reasons can be accurately and timely diagnosed, motorcade management is optimized, and operation cost is reduced.

The invention belongs to the field of automobile intelligent management, and particularly relates to a vehicle tree interface optimization method for motorcade management, which comprises the following steps of: 1, constructing a vehicle tree data structure, and storing all vehicle node objects in a dictionary; 2, various vehicle states, a state display priority rule, a state propagation rule and a local sorting rule are defined, and according to the state propagation rule, when the states of vehicle nodes change, state change information is propagated upwards step by step along the recursive nested data structure; step 3, when the vehicle node changes, generating a local refreshing instruction according to the vehicle node change information, updating statistical information according to a state propagation rule, and notifying a UI layer to refresh through an agent mechanism; and step 4, dynamic unfolding and folding of grouping nodes, rapid searching and screening of vehicles and groups and batch management operation are realized based on a multi-stage TableView auxiliary class. The problems of low vehicle state refreshing efficiency and low display sorting efficiency when the data volume is large are solved.

The invention relates to a vehicle active safety early warning device and early warning method based on a call center, and the early warning device comprises a vehicle-mounted equipment module, a data analysis server, and a call center module. The vehicle-mounted equipment module is composed of an MCU control unit, a GNSS positioning module, a driver visual recognition module, a lateral blind area early warning module, a forward collision early warning module and a 4G communication module. A vehicle positioning database, a vehicle early warning database, a data analysis engine and an Internet of Vehicles data gateway are installed in the data analysis server; the call center module is composed of a telephone traffic center server SIP switch and a mobile terminal. The vehicle-mounted equipment module is connected with a vehicle networking data gateway of the data analysis server through the 4G communication module, and the data analysis server is connected with a telephone traffic center server of the call center module through an intranet communication network cable. The system has the advantages that the real-time monitoring and active early warning of the vehicle safety state are realized, the motorcade management efficiency is improved, and the driving safety is guaranteed.

The invention provides a method for automatically monitoring and identifying dangerous driving behaviors based on a driving scene, and the method achieves the comprehensive monitoring of a vehicle driving state and a vehicle driving road section through the installation of a satellite positioning device, the collection of CAN bus data, the deployment of high-precision map road network data, and the data fusion. By setting a behavior threshold value and combining time sequence analysis and map data, the judgment accuracy is enhanced, a real-time monitoring algorithm engine is developed, and dangerous driving behaviors are accurately monitored and recognized in a complex and changeable driving scene. According to the method, dangerous driving behaviors of the driver can be corrected in time, dangerous driving events are recorded and managed at the same time, the running safety risk is reduced, the driving safety is improved, and losses caused by traffic accidents are reduced. Various dangerous driving scenes are covered, a driver is helped to reasonably control the vehicle speed, digitization of motorcade management and transparency of risk management are achieved, and the requirement for supervision compliance is met.

A fleet of all-electric, battery powered industrial or commercial mobile power units (MPUs) or equipment is provided. Systems and methods for managing the fleet of equipment is also provided. Observable data, such as i) equipment performance and health data, ii) electricity cost data, iii) telematic data, and iv) scheduling data, can be used by machine learning models to optimize fleet management and decision making. The machine learning model can be configured to generate suggested actions, commands, or decisions which are transmitted to fleet managers who are responsible for activities such as i) equipment charging and maintenance, ii) equipment delivery logistics, and iii) rental pricing strategy. Feedback data from the outcome of these decisions, or the completion of the related activities, can tracked and used to update the machine learning model. Interactive portals may also be utilized by customers to make reservations and managers to manage reservations, monitor the fleet of equipment and provide support to MPUs across the product lifecycle.

A system receives vehicle metric data from a gateway device connected to a vehicle. The vehicle gateway device gathers data related to operation of the vehicle and / or location data. The system receives data from multiple vehicles in a fleet. The vehicle gateway device gathers vehicle metric data at a high frequency. Instead of transmitting a large amount of vehicle metric data at a fine level of granularity, the vehicle gateway device aggregates and buckets the vehicle metric data over a period of time (such as, every five minutes). The system uses the bucketed data for fleet management analysis.

The invention discloses a multi-level encryption authentication and data integrity protection method in a vehicle cloud communication environment, and aims to guarantee communication security between an electric vehicle and a cloud platform. According to the method, a unique digital certificate is allocated to each electric vehicle, and identity verification of a vehicle end and a cloud platform is realized in combination with a two-way TLS handshake protocol. In the data transmission process, the transmission content is encrypted by adopting a symmetric encryption algorithm, so that the confidentiality of the data is ensured. Meanwhile, the integrity of information in the data transmission process is ensured by using a digital signature technology, and tampering is prevented. And if the data verification fails, an early warning mechanism is triggered, and abnormal information is fed back to a related supervision platform through the V2X communication system, so that instant response and fault positioning are realized. According to the method, potential safety hazards such as man-in-the-middle attack and data leakage in the communication process can be effectively prevented, and the safety and data integrity of an Internet of Vehicles system are improved. The method is widely applied to scenes such as intelligent transportation, motorcade management and electric vehicle remote monitoring.

A system and method for artificial intelligence enhanced mobile energy and data and network control, planning and optimization. The present invention relates to a system and method for optimizing energy and data and network use in mobile platforms, such as facilities, vehicles, tools, and devices. The system leverages AI, data analytics, and context-aware techniques to collect, process, and analyze data from various sources, including sensors, weather data, and spatial and temporal data with locality aware computing, transport, storage and networking across assets that may be owned or operated by multiple stakeholders. By considering a variety of factors, the system generates optimized recommendations for data storage, compute, transmission, device settings, fleet management, and physical and virtual route planning and logic locality planning. The invention offers benefits, including improved energy efficiency, enhanced data and network management, increased operational efficiency, and cost savings.

A method of operating a fleet optimization system to optimize operation of a fleet of vehicles is provided. The method includes determining a dispatch and routing plan for a fleet of vehicles, and providing the dispatch and routing plan to a fleet management system. The method includes receiving feedback parameters indicating energy / fuel consumption of the fleet operating according to the dispatch and routing plan, and further determining an energy consumption probability distribution for the fleet in response to the feedback parameters. Using the energy consumption probability distribution, the method determines an updated dispatch and routing plan for the fleet of vehicles to optimize delivery and energy consumption objectives.

Embodiments described herein provide a localization mechanism that blends location data collected from hardware sensors equipped with a personal mobile vehicle and location and / or status data collected from external location source other than the personal mobile vehicle to generate adjusted location data for the personal mobile vehicle.

Systems, apparatus, and methods for emergency charging. Within the context of an EV fleet depot, the fleet vehicles are typically owned / controlled by a company or organization which has an interest in communal resource allocation. The communal resource management considerations of vehicle fleets create new opportunities for resource allocation which are not readily available to e.g., individual consumers. Various aspects of the present disclosure are directed to shared communication protocols within a fleet of vehicles that facilitate efficient resource allocation. Communication and evaluation may be formalized according to a shared rule set and metrics (promulgated by the fleet authority, etc.). Various aspects of the present disclosure may further extend the concepts of priority and / or severity to site-wide power management. Conceptually, power may be distributed to power a first priority, before distributing the remaining power to the next priority, etc. This isolates the first prioritization level from internal and / or external throttling.

The invention relates to the technical field of motorcade management systems, and discloses a motorcade intelligent scheduling decision-making and monitoring management system and method combined with a car roof holder, and the system comprises a management server and a vehicle-mounted terminal, and the vehicle-mounted terminal collects a space monitoring abnormal value; the management server obtains a motorcade business value cardinal number, a business performance path and a real-time position coordinate, determines a corresponding vehicle business performance rigidity coefficient, and calculates a business performance deviation degree; according to the method, a dynamic adjustment mechanism of a macroscopic business performance state to a bottom layer physical sensing signal is established, ineffective triggering caused by bottom layer environment fluctuation is inhibited when the business state height is determined, and the weight correction parameter of the car roof pan-tilt is generated according to the business performance rigidity coefficient and the business performance deviation degree. Supervision resources are accurately focused on the substantial default risk, and the resource configuration efficiency of whole motorcade scheduling management is improved.

An automatic personal enhancement system that is tailored to each user's special access needs. The system having a multimedia presentation device, an onsite node having a user protocol time code message protocol, and the system sending a real-time time-code to the system, over a private LAN, a transmission device to transmit information to the onsite node, a fleet management subsystem, a content database server, a smart device, and a web server. The web server having instructions for: identifying a user entering a venue; connecting to the show control subsystem; selecting a language for multimedia pretensions from the show control subsystem; tracking the user's smart device with the personal enhancement system for automatically playing multimedia associated with the location in the venue in proximity to the user's smart device; and stopping the tracking and disconnecting the personal enhancement system from the user's smart device after the user exits the venue.

Fleet management of unmanned aerial vehicles (UAVs) is disclosed. Fleet management systems and methods may be implemented within UAVs, or systems utilizing UAVs, utilized in a delivery system configured to pick up a payload or a package at a shipping location and deliver a payload or package to a delivery location. The fleet management systems and methods may facilitate system operations of a UAV fleet, including, without limitation, positioning or deploying UAVs to meet or fill demand, prepositioning UAVs to meet a demand prediction, association delivery' orders to UAVs, order fulfillment, fleet maintenance management during operations, and flight path planning or generation.

Embodiments detect stops by an entity on a pre-planned trip including a plurality of stops and a planned sequence of stops, each stop including a geofence boundary. For each stop, embodiments add an arrival transition region extending inward from the geofence boundary. Embodiments receive a first geo-location message indicating a first location and corresponding to a first time for the entity and determine whether the first location falls within a first arrival transition region corresponding to a first stop having a first geofence boundary. When the first location falls within the first arrival transition region, embodiments wait for a predefined transitional time period. During the predefined transitional time period, when a second geo-location message is received indicating a second location inside the first geofence boundary and outside the first arrival transition region, the first time is determined to be an arrival time for the first stop.

An automation system manages operations of a fleet of robotic devices at a construction site. The system receives a construction plan including site data and a list of tasks with dependencies. Based on the plan, the system generates a virtual representation of the construction site and allocates tasks to individual robotic devices. Each robotic device transmits operational status data and sensor data, which is received by the system and used to update the virtual representation. The updated representation reflects the status of each task and incorporates real-time site information. The system generates a visualization of the virtual representation and transmits it to a client device operated by a user, causing the visualization to be presented on the client device.

The invention relates to the technical field of state monitoring of new energy trucks, and particularly discloses a real-time online monitoring system for the running state of a new energy truck and a working method.The system is characterized in that a vehicle-mounted sensor is connected with a vehicle-mounted controller, the vehicle-mounted controller is connected with a vehicle CAN bus system, the vehicle CAN bus system is connected with a vehicle-mounted wireless terminal, and the vehicle-mounted wireless terminal is wirelessly connected with a mobile phone APP; computational logic is built in the mobile phone APP; vehicle state information recognized by the vehicle-mounted sensor is sent to the vehicle-mounted controller in an electric signal mode; the vehicle-mounted controller identifies the electric signal and forms message information, the vehicle-mounted controller informs a vehicle CAN bus system of the current state of the whole vehicle by sending the message information, and the vehicle-mounted wireless terminal reads the state information; the vehicle-mounted wireless terminal transmits the information to the mobile phone APP through a wireless signal and displays the information in a page; according to the invention, the user and the motorcade management background can conveniently know the real-time state of the vehicle, and the management of the vehicle and the use of the user are greatly facilitated.

A production plannings of products and goods or shop floor logistics in producing, trading or distributing products / goods is provided in which it is addressed to maintain or keep data about the production planning of the products and goods or the shop floor regarding the logistics in producing, trading or distributing the products and goods up to date, and at least one mobile logistics robot to automate a logistic transport of the products, the goods or production material for the products and goods within a shop floor is equipped each with a sensor technology appropriate to measure or capture and control a current state or changes of the shop floor by sensor data, when each the robot is managed by a fleet management system for distributing or scheduling logistic tasks among the at least one robot executing transport tasks of a transport task queue maintained by an automated logistics planning system.

The invention relates to a fleet management system. A method implemented by a computing device of monitoring a set of machines. The method includes receiving a plurality of candidate statistical distributions for a set of machines. Each of the plurality of candidate statistical distributions describes first operational data and second operational data characterizing one or more aspects of at least one machine in the set of machines. The method further includes updating and comparing the plurality of candidate statistical distributions based on a combination of the first operational data and the second operational data. The method further includes selecting a baseline statistical distribution from the plurality of candidate statistical distributions based on the comparison. Further, the method includes outputting a baseline statistical distribution, where the baseline statistical distribution is predicted to optimally describe both the first operational data and the second operational data, and sending an alert to indicate the found baseline statistical distribution.

The invention relates to a method for managing a fleet of unmanned vehicles (5) by means of a computer system (1) comprising a supervisor (2) connected to a user interface (3) and a mission manager (4) that controls the movements of the vehicles. The invention also relates to a computer system (1) implementing such a method. Figure for the abstract: 1

Techniques described herein relate to controlling and / or influencing routes driven by vehicles (autonomous or other vehicles, e.g., vehicles in a fleet managed by a fleet management system). In some cases, the techniques described herein involve centrally generating road weights using a remote system, such as a fleet management system, and providing these pre-calculated weights to vehicles to simplify on-board routing. In contrast to sending a large amount of raw traffic, road conditions, and other data to each vehicle, the remote system pre-processes the data into compressed road weights that are optimized for route planning. The architecture provides various technical advantages, such as reduced data transmission, reduced computational load on the vehicle, and decentralized control of route planning of the entire fleet.

Methods, systems, and computer programs are presented for immobilizing a vehicle based on the detection of threats, such as tampering or jamming. The method includes configuring a vehicle for tamper and jamming detection, installing a communication device and an engine immobilizer in the vehicle, and providing a user interface for configuring the communication device to activate the engine immobilizer. The method further includes parallel paths for tampering detection, which immobilizes the vehicle and notifies the server upon detection, and for jamming detection, which similarly immobilizes the vehicle and notifies the server, including the vehicle's GPS position. Optionally, image information from the vehicle may be included in the notification or to trigger immobilization upon detecting multiple occupants, indicating a potential carjacking. This solution enables fleet managers to react to thefts and maximize vehicle recovery rates quickly.