Classifications

• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
  • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
  • G06F16/29—Geographical information databases
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
  • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
  • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
  • G01C21/34—Route searching; Route guidance
  • G01C21/36—Input/output arrangements for on-board computers
  • G01C21/3679—Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
  • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
  • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
  • G01C21/34—Route searching; Route guidance
  • G01C21/36—Input/output arrangements for on-board computers
  • G01C21/3697—Output of additional, non-guidance related information, e.g. low fuel level
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
  • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
  • G01C21/38—Electronic maps specially adapted for navigation; Updating thereof
  • G01C21/3804—Creation or updating of map data
  • G01C21/3807—Creation or updating of map data characterised by the type of data
  • G01C21/3811—Point data, e.g. Point of Interest [POI]
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q10/00—Administration; Management
  • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
  • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q10/00—Administration; Management
  • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
  • G06Q10/063—Operations research, analysis or management
• • G06Q50/40—
• • G—PHYSICS
  • G07—CHECKING-DEVICES
  • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
  • G07C5/00—Registering or indicating the working of vehicles
  • G07C5/008—Registering or indicating the working of vehicles communicating information to a remotely located station
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
  • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
  • G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
  • G08G1/0125—Traffic data processing
  • G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
• • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
  • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
  • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
  • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Definitions

• POI mobile property points of interests
• MPs mobile property
• MPs' specific services such as replacing gas bottles, water replenishment, discharging waste water and toilet waste, 220V electric connection, engine fuel replenishment.
• US8013759 describes a transmitter unit having a housing adapted to be coupled in association with a trailing vehicle.
• the housing also has a multiple axis accelerometer adapted to sense the status of the transmitter unit and a trailing vehicle.
• the housing also has electronic components coupled with the accelerometer.
• a receiver unit has a housing adapted to be coupled in association with a leading vehicle. A user in audio proximity to the receiver unit is wirelessly signaled in the event of an anomaly at the transmitter unit.
• GB2396729 describes a remote monitoring security system for mobile property (such as boat, aeroplane, helicopter, caravan, motor car, lorry etc.) comprising a plurality of sensors for detecting the status of respective functional elements (preferably safety or security- sensitive elements), means for processing the signals generated by the sensors to determine the security status of the property and remote signaling means for periodically transmitting to a receiving station (e.g. the user's mobile telephone) at least one status report based on the signals from the sensors.
• a receiving station e.g. the user's mobile telephone
• DE202006010816 describes a communication device with an antenna for sending a command signal to a refrigerator, air conditioner, roof opening and lighting switch receiver.
• the communication device has a receiving unit that receives a radio signal from the refrigerator, air conditioner, roof opening and lighting switch receiver.
• the refrigerator, air conditioner, roof opening and lighting switch receiver are assigned to a controller that detects a parameter at a location of the refrigerator, air conditioner, roof opening and lighting switch receiver.
• Integrated intelligent in-vehicle control and management system solve technical problem of lack of information control related to mobile property (hereinafter MP) points of interests (hereinafter POI) data comprising mobile property (hereinafter MP, plural MPs) specific needs and interests, such as parking places, overnight stays and camps for MPs, as well as MPs' specific services, such as replacing gas bottles, water replenishment, discharging waste water and toilet waste, 220V electric connection by securing, collecting, and providing POI data, said POI data to be accessible via user-to-vehicle connection, or via use of available public or private network connections.
• MP points of interests
• POI Point of Interest is meant, which usually refers to geo-spatial places that are of interest of particular user or vehicle. For example when using cars, users are interested in gas stations, Shopping malls, tourist attractions, etc. When using recreational vehicles, more prominent POIs are service points, camps, camping places, etc. When using boats, POIs are marinas as well. When using airplanes or helicopters, POIs are airports and landing spots.
• Subject of this invention is the process to automatically populate empty POI database and/or improve the existing database with new relevant data.
• the process is comprised of three main steps, with the fourth optional improvement that supports intra-vehicle detection, where more than one mobile unit contributes to the process:
• SPD Staypoint Detection
• RSVA Resource Sensor Values Attachment
• IVA Intra-vehicle alignment
• Subject of this invention is also integrated intelligent in-vehicle control and management system, for use in mobile property (MP), by user of said mobile property, wherein said system is comprised of at least one point of interest (POI) or plurality thereof detection device, said point of interest comprising entry into POI database comprising information chosen from the group containing information on parking place for MP, overnight stay for MP, camp for MP, MP specific services chosen from the group containing replacing gas bottles, water replenishment, discharging waste water, discharging toilet waste, 220V electric connection, plurality and/or combination thereof; wherein said database is either public or private database; wherein said system further comprises at least one I/O module for handling the communication with at least one on-board device chosen from the group containing at least one sensor, said sensor chosen from the group containing accelerometer, gyroscope, pressure sensor, temperature sensor, location sensor, preferably GPS or similar location sensor, plurality and/or combination thereof;
• said system further comprises at least one computational module for storing information on state of said system handling application logic and communicating with at least one user interface; wherein said computational module further synchronizes said sate of said system with a server, preferably HTTP or HTTP-like server, said server enabling said user to control said system from location chosen from the group containing visual proximity location, radio range location, LTE range location, remote location accessible via network, plurality and/or combination thereof.
• a server preferably HTTP or HTTP-like server
• Subject of this invention is further integrated intelligent in-vehicle control and management system wherein said at least one I/O module and said at least one computational module are connected in parallel, and communicate via serial communication.
• Subject of this invention is further integrated intelligent in-vehicle control and management system wherein said application logic is executed on said computational module, said application logic allowing for functions chosen from the group containing smart monitoring, setting dynamic and static alarms, remote warnings and notifications, resource consumption monitoring, resource consumption predictions, storing historical resource consumption for showing historical charts, autonomous decisions and behavior, plurality and/or combination thereof.
• Subject of this invention is further integrated intelligent in-vehicle control and management system wherein said remote location accessible via network is within range of a network using any wireless communication standard, preferably chosen from the group containing LTE, 5G, 4G, GSM, radio network, plurality and/or combination thereof, said network used for communication for transmitting messages to said at least one user interface.
• any wireless communication standard preferably chosen from the group containing LTE, 5G, 4G, GSM, radio network, plurality and/or combination thereof, said network used for communication for transmitting messages to said at least one user interface.
• Subject of this invention is further integrated intelligent in-vehicle control and management system wherein said radio range location is within range of radio communication for transmitting messages to said at least one user interface.
• Subject of this invention is further integrated intelligent in-vehicle control and management system wherein said at least one I/O module is comprised of at least one input/output block, radio transmitter, radio receiver, said input/output block comprising at least one block chosen from the group containing LIN block, CAN block, analog input block, analog output block, digital input block, digital output block, said at least one sensor, said at least one sensor attached directly onto the board, plurality and/or combination thereof.
• said at least one I/O module is comprised of at least one input/output block, radio transmitter, radio receiver, said input/output block comprising at least one block chosen from the group containing LIN block, CAN block, analog input block, analog output block, digital input block, digital output block, said at least one sensor, said at least one sensor attached directly onto the board, plurality and/or combination thereof.
• Subject of this invention is further integrated intelligent in-vehicle control and management system wherein said computing module is comprised of at least one block chosen from the group containing application processor block running a time-sharing operating system, memory block, storage block, location detection block, communication block, plurality and/or combination thereof.
• Subject of this invention is further integrated intelligent in-vehicle control and management system wherein said communication block is chosen from the group containing long-range communication block, short-range communication block, plurality and/or combination thereof; wherein said long-range communication block is chosen from any wireless communication standard, preferably chosen from the group containing LTE, 5G, 4G, GSM, radio network, plurality and/or combination thereof; wherein said short-range communication block is chosen from the group containing radio, Bluetooth, Wi-Fi, plurality and/or combination thereof.
• Subject of this invention is further integrated intelligent in-vehicle control and management system wherein said computational model further provides for automated POI learning, said automated POI learning using data as provided by any of above referenced module, block, sensor, plurality and/or combination thereof.
• Subject of this invention is also a method for automated point of interest (POI) or plurality thereof learning using integrated intelligent in-vehicle control and management system according to any of the previous claims, said method for automated POI or plurality thereof learning comprising the following steps:
• Subject of this invention is further method for automated point of interest (POI) or plurality learning wherein said data are obtained from a source chosen from the group containing single user with single visit, single user with multiple visit, multiple user with singe visit, multiple user with multiple visit, whole population, plurality and/or combination thereof.
• POI point of interest
• Subject of this invention is further method for automated point of interest (POI) or plurality learning wherein automated point of interest (POI) or plurality thereof learning wherein said harvesting of data comprise detecting of change in at least one resource, said resource chosen from the group parking place for MP, overnight stay for MP, camp for MP, MP specific services chosen from the group containing replacing gas bottles, water replenishment, discharging waste water, discharging toilet waste, 220V electric connection, plurality and/or combination thereof; wherein said at least one resource is linked to POL
• Subject of this invention is also use of point of interest (POI) or plurality thereof data by means of integrated intelligent in-vehicle control and management system as described above, said POI or plurality thereof data obtained by method for automated point of interest (POI) or plurality thereof learning as described above.
• POI point of interest
• POI point of interest
• plurality thereof data obtained by method for automated point of interest (POI) or plurality thereof learning as described above.
• Mobile properties such as motorhomes and caravans (together with towing vehicles) are bigger and consequently slower vehicles, which especially during holidays, contribute to the congestions on the highways, other roads, especially in cities, towns and touristic areas, and parking places.
• a mobile property has bigger complexity because of various road limits, parking place and camp limits. They search for/need additional infrastructure on gas stations (waste disposal, electricity, availability of gas), public modes of travelling in the cities for local transport, etc. while they are subject also to problems of safety. For purposes of this specifications, such locations are called staypoints.
• users of these vehicles already tend to connect to sorts of informal networks and commonly travel and park in groups (also from safety reasons) and therefore they need information on commonly used stay points, especially ovemight-ones.
• controlling and management of mobile properties their internal systems and appliances are also in rapid development.
• POI points of interest
• MPs mobile properties’
• MPs' specific services such as replacing gas bottles, water replenishment, discharging waste water and toilet waste, 220V electric connection, etc. All these POIs or better to say their current usage according to user needs should be presented to him/her in an intelligent yet simple way.
• Data feeds from a vehicle may include internal sensors for water, gas for heating, electricity, etc., as well as external sensors for temperature, air humidity, light level, GNSS data of the car.
• GNSS Global Navigation Satellite System
• OBD2 data from base vehicle can also be used.
• OBD stands for On-board Diagnostics data.
• the primary intended recipients of the services are users of mobile properties such as motorhomes and caravans- while the services are in general possible for any car driver (personal cars, truck drivers etc.) and also other mobile property (boats, yachts), especially when operating in unknown environments.
• Integrated intelligent in-vehicle control and management system thus enables communication and control of in-vehicle systems, communication to the outside world, i.e. with a central platform, with the infrastructure around them, with smart networks, via any wireless communication standard, preferably chosen from the group containing LTE, 5G, 4G, GSM, radio network, plurality and/or combination thereof GSM etc.
• any wireless communication standard preferably chosen from the group containing LTE, 5G, 4G, GSM, radio network, plurality and/or combination thereof GSM etc.
• Traveler Information Services TIS
• general and specific for mobile property users (various POIs etc.), on-route and on-site,
• ⁇ AI features should include provision of cognitive behavior of the vehicle towards the traveler, including vehicle self-aware subsystems control, monitoring and prediction, intelligent and personalized route planning including tourist route spots, current traffic and camping places states, specific MP service related POIs with regard to the current need and state of MP, and MP to the operating center connection and monitoring,
• Control and support center that allows for additional services for online vehicle monitoring, maintenance and support, as well as central storage and processing of data with specific advices and services offered back to the users.
• Such a system is able to connect multiple systems, collect data from several data sources, communicate with central system, analyses the data locally as well as get relevant higher level outputs from central system, and exposes the functionalities to mobile property users through an application. It permits a tighter integration of mobile property specifics (points of interest, weight/size limits, and internal sensors of the mobile property, vacation/trip planning POIs). So the mobile property community is provided with an important missing part of Traveler Information Services (TIS) that benefits users, as well as mobile property producers.
• TIS Traveler Information Services
• the invention presents bi-modular remote control and monitoring system for mobile property. It is comprised of an I/O module that handles the communication with the on-board devices and a computational module that stores the state, history of the state, handles the application logic and communicates with one or more user interfaces.
• the computational module also synchronizes the systems’ state with an HTTP-like server that enables the user to control the mobile unit from any remote location with an internet connection.
• the invention can be organized into two configurations (i.e. the basic and autonomous configuration) which differ mainly in the level of autonomy, communication capabilities and monitoring capabilities. While the basic configuration only allows for remote control when in close proximity to the mobile unit, the autonomous configuration can be controlled from distant locations (anywhere in the world) and can be used as a remote control system with advanced resource monitoring.
• both modules are connected in parallel and communicate via serial communication (UART or similar).
• the application logic is executed on the computational module and allows for smart monitoring, setting dynamic and static alarms, remote warnings and notifications, resource consumption monitoring, resource consumption predictions, storing historical resource consumption for showing historical charts, autonomous decisions and behavior, etc.
• a key advantage of the proposed invention is the ability to control the mobile unit at large distances while also offering the same interaction at short distances when the vehicle does not have long range signal.
• the communication is routed through a HTTP-like server and sent to the on-board module via LTE-like connection.
• one of the on-board radio units is used to transmit the messages to the user interface.
• the basic configuration uses the I/O module to relay device messages (i.e. LIN, CAN, etc.) directly to a mobile device which hosts the application logic.
• the main advantage of the basic configuration is its price efficiency and low energy consumption.
• the I/O module is comprised of one or more input/output block and a radio transmitter and receiver.
• the input/output blocks may include one or more LIN blocks, a CAN block, analog input blocks, analog output blocks, digital input blocks, digital output blocks and can also include sensors attached directly onto the board like an accelerometer and gyroscope which can be used for levelling or other solutions, a pressure sensor, temperature sensor, etc.
• the radio transmitter and receiver functions as the communication channel when the invention is in the basic configuration which transmits device messages from the device to the mobile device (e.g. smartphone). In the autonomous configuration, the radio can be dormant or can be used as an additional channel to communicate with the user interfaces.
• the computing module is comprised of an application processor block running a time sharing operating system, one or more memory and/or storage blocks, a location detection block and one or more communication blocks.
• the storage blocks act as a buffer to store historical values, user messages, notifications, and to store and persist application data.
• the communication blocks are comprised of one or more long-range communication blocks such as any wireless communication standard, preferably chosen from the group containing LTE, 5G, 4G, GSM, radio network, plurality and/or combination thereof but may also include short-range communication blocks. The latter may include, but are not limited to, radio technologies such as Bluetooth, Wi-Fi, etc.
• automatic POI learning is learning from the data provided by the invention described above. This can be done inside the device (computational block) or outside (backend server).
• the GPS and sensory data are analyzed by the process (machine learning, statistical, or rule-based).
• the results are clustered into the stay points with attached sensor value changes and their times. These points can be then additionally clustered into the POI points. This is done either across single user with multiple visits, or across multiple users or whole populations.
• the sensor values are used to detect changes in the resources, which is linked to the stay points and POI locations and serves as a detection whether specific location has particular resource availability (water, gas, electricity, waste-water facilities). The sensor values can also help with the detection whether the location is a POI or not.
• the repetitions and time of stay is used to assess the confidence of the location and the data about it.
• the same data is also used to assess the popularity of the location and when combined with personal data can provide the smart suggestions for where to go next.
• Method in accordance with this invention is comprised of three main steps, with the fourth, optional, one.
• Step 1 is shown in Fig. 1, and employs on the data flow from GNSS module (GPS, Galileo, ...) or other location sensing hardware (cell-tower, Wi-Fi, ... ) (1).
• GNSS module GPS, Galileo, ...) or other location sensing hardware (cell-tower, Wi-Fi, ... ) (1).
• the GNSS data-flow must be directed into the processing module (3), or stored for later, if the processing is not being done in real-time.
• the GNSS hardware can be integrated or mounted on the mobile unit (vehicle), or it could be provided by a person or something (such as device, or remote device) else located inside, or nearby the mobile unit. For example, occupant’s mobile phone with GNSS sensor.
• the GNSS When the GNSS is part of the vehicle, then it can be connected directly to the processing module (3), or indirectly through the communication module (4). In the case when it is not part of the vehicle (like the example of occupants phones), it has to be connected to the processing unit through the communication module.
• the module performs the stay point detection (SPD) process.
• SPD stay point detection
• any of the existing, or custom SPD, location detection, location clustering or trajectory detection processes can be used (for example: [1, 2, 3, 4, 5...].
• the actual implementation of the process matters to the point of the detection speed and quality.
• the choice of the detection process also dictates the energy consumption of the processing module.
• the simplest possible process for this use is called“Time-based clustering algorithm” [1] and will be used in this document as an example of how to integrate all the steps into the full POI detection process. This choice is also optimal for good quality of the data that is coming from our hardware in the implemented solution.
• Figure 1 shows the basic principle of the example (and many other) SPD processes.
• the processing module calculates the distance and time between the geo-spatial data-points coming into the processing module, and checking if the distance between the first and the last point is less than Td, or distance threshold. Once this is not true anymore, it checks the time span of all the points inside the same distance threshold. If that time span is longer than Tt or Time Threshold, then that group of the points can be considered a “staypoint”.
• GNSS module (1) The minimal requirement of the data coming from GNSS module (1) for SPD detection are geo-spatial coordinates (Latitude, Longitude). This can be additionally improved by adding more GNSS information to the data flow, such as:
• the detected staypoint at the end consists of its center, radius, contour (in more advanced processes), time of arrival (in the case of post-processing and not using real-time data, the time of leave and stay duration are also attached), and can also have all of the original raw data attached for the reference.
• An example of two detected staypoints on the same location from multiple GPS coordinates is shown in Fig. 2.
• Step 2 the detected staypoint is used to query for existing nearby POIs in the database by staypoint mapping means which in preferred embodiment can be performed by processing module (3). If there is no existing data, then the new initial POI is created from the SPD from step 1. If there is existing POI data, the detected SPD is mapped to one of the existing POI locations, as one more visit. The processing module now has a link between this particular visit from Step 1 and the POI location.
• FIG. 3 shows a) staypoint attachment to the existing POI location, b) Creation of new POI location from new staypoint. This step can also be performed by means of processing module (3) or by some other dedicated hardware able to query for existing nearby POI in the database.
• the attachment, or new POI creation can employ many different processes to do the same job, with different levels of complexity, memory consumption and computational intensity.
• the simplest approach to attach the staypoint to the existing location is to calculate the distance between the SP center and nearby POI locations (from the center or from the contour) and pick the closest. If there is multiple POI locations within similar distance threshold, then the similarity between the other fields in the SP data can be calculated (altitude, Wi-Fi and BT signals, time of arrival, Nearby phone cell towers ).
• step 3 this is performed by comparison means which in preferred embodiment is comprised of the processing module (3) listening for the updates from GNSS module (1) and IO/sensory module for resource measurements (2), and also the optional communication module (4), until the signal comes from the step 1, that the staypoint is closed (the vehicle leaves the location).
• the processing module is comparing the data between the existing POI (or newly created one), and the data that is coming in and is attached to the staypoint. This can consist of, but is not limited to any of the following updates given as an example:
• Step 3 and Step 1 can be running in parallel, where the data from step 3 is helping with the Staypoint identification. If the Staypoint is identified the process continues as normal, if not, the data from step 3 is discarded, and the process is repeated until the SPD is detected.
• the simplest example of the transfer/attachment (which can serve to explain the process) is that the sensors are separated (by the processing unit) into three categories regarding the data aggregation:
• Boolean (Rising edge): The attachment will add“True” value to the POI, if the level of measured resource increased over the specified threshold during the staypoint duration. From the example, the following sensors are of this type: o Fresh water level, Connected mains power, Heating Gas, Fuel level, Cooling liquid level, Air pressure in the tires, Windshield cleaning fluid levels
• Boolean (Falling edge): The attachment will add“True” value to the POI, if the level of measured resource decreased over the specified threshold during the staypoint duration. From the example, the following are of this type:
• Average value The attachment will calculate average value during the whole staypoint duration, and add it to the running average value at the POI. From the example, all the rest of the sensors which are not listed within Boolean types, are of this type.
• each update to the sensor influences the POI database, adding a new average number for the measured resource to the POI data, or True value for the resources that are available at the POI, or for the resources for which the POI might have the dump facilities (the ability to get rid of the waste water, as an example).
• step 1 it is possible to see how the staypoint is detected (step 1) when the time reaches threshold Tt, while the GPS coordinates are within the Td.
• Tt threshold
• the GPS coordinates are within the Td.
• water and waste water cannot speed up the detection, because the system is losing the clean water and gaining waste water, which can happen also outside of the POI location.
• the step 2 After the staypoint is detected (at Tt), the step 2 either attaches to the existing POI, or it creates a new POI location. After that, the Step 3 is executed immediately on all the data, and then consequently on each new data point, until the“end of the staypoint”, which is detected by step 1.
• This new information is then attached to the POI location, together with its detection time.
• the steps 1 to 3 can happen completely locally on the vehicle/mobile unit itself, even if there is no communication module (4).
• the mobile unit is growing its own POI locations, independently of the rest of the world, and can be used locally by the users, or by the processing module to perform some other tasks such as control, autonomous behavior, etc., more intelligently.
• Figure 5 shows results of the step 3.
• the locally detected POI data can be sent to the Step 4, to maintain and grow a global POI database.
• This hardware set-up is depicted on Figure 8.
• Optional step 4 is performed after the data from the step 3 is attached to the POI location, the results (the last POI, or all of them) can be published to the remote server for global processing. This is can be done as an optional step, if the hardware implementation of the process has communication module (4).
• This step also comprises grouping data from several sources, preferably several vehicles into main data. This is similar to Staypoint detection step but with more than one vehicle, comprising the following steps:
• At least one POI of the first vehicle is identified by processing module (3) of any of vehicles engaged into point of interest (POI) or plurality learning,
• At least one corresponding POI of at least one another vehicle is identified by processing module (3) of any of vehicles engaged into point of interest (POI) or plurality learning;
• data are combined in to single union, and uploaded into common database by processing module (3) of any of vehicles engaged into point of interest (POI) or plurality learning.
• POI point of interest
• POI A of vehicle 1 has 10 visits, and data on X and Y,
• both of detected POIs are considered close enough (e.g. closer than 100 meters) when POI has been identified, so data from both vehicles are merged and reported back to global database as POI A with 13 visits (i.e. 10 + 3), and data on X, Y, and Z.
• the server based application first distinguishes personal POI points (home, private place, personal with the public ones. Similarly as with the rest of the steps, there is infinite number of ways to detect this, the simplest one is, the rule that multiple different mobile units/users need to detect the same location. This is depicted on the Figure 6, where we can see that the place POI2 which was detected by only one mobile unit is marked as private, but POI1, which was detected by multiple mobile units (2 in the example case), is marked as public POI.
• Fig. 6 shows distinguishing between public and private POI detections.
• Fig. 6 also shows how the learned information about the POI location from multiple mobile units is merged into the common data-base. From the example, vehicle 1 only detected the electricity availability, and visited the POI location 3 times, and vehicle 3 only detected fresh water availability through 2 visits. In the cloud infrastructure this information is merged, as POI1 has 5 visits and information about electricity and water availability, which came from different mobile units local detections (steps 1 to 3).
• this process also proposes how to handle the changes in the POI locations infrastructure.
• the POI location owners added some extra infrastructure (for example, installed waste water dump facilities), as this will get detected by the process. But it is harder to detect when some infrastructure stops working, or when the POI location becomes permanently closed. This can be mitigated by employing a “cooling” mechanism, or a time threshold, when particular resource, or whole POI was last detected/visited ( Figure 6 shows that detected resources have also an information of the time of the detection). If this becomes over some threshold, the system can mark the particular POI, or resource as deleted, or as“requires human attention”.
• Figure 7 shows schematics of the system for automatic learning and maintenance of POI databases, consisting of mobile unit with GNSS module (1), IO/sensory module for resource measurements (2), processing module (3), and optional communication module (4) and global processing module (5).
• Figure 8 shows one possible hardware implementation of the system. It consists of 2 circuit boards. Basic (lower one), and App (upper one). The bottom one, representing the IO/sensory module for resource measurements (2) can operate independently as the hardware for remote control and monitoring. For this it requires external processing unit (such as mobile phone, or App circuit board), this is why this implementation example has all the signals forwarded to Bluetooth, and to the connector which is prepared for the second circuit board.
• the App board has all of the other modules (from Figure 7).

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• 2019
  • 2019-07-27 WO PCT/SI2019/050013 patent/WO2021021029A1/en unknown
  • 2019-07-27 EP EP19765341.3A patent/EP4004763A1/de not_active Withdrawn

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