Procedure for operating a safety device and safety device for a loading area

Abstract

Method for operating a safety device (20) for a loading area (4), preferably within a densely built-up area and / or an urban area and particularly preferably within a city center, for at least partially automatic, preferably fully automatic, monitoring of a transfer of goods between a delivery vehicle (2) for transporting the goods to be transferred and the loading area (4), wherein the safety device (20) performs the monitoring depending on at least one monitoring parameter, wherein the monitoring parameter is characteristic of monitoring data acquired by means of at least one monitoring device (22) for monitoring the loading area (4) with regard to the transfer of the goods to be transferred, wherein the monitoring data results from the acquisition of a delivery process of the goods to be transferred by means of the at least one monitoring device (22), characterized in thatthat the safety device (20) determines at least one target delivery quantity with regard to the transfer of the goods to be transferred and compares it with an actual delivery quantity determined on the basis of the at least one monitoring quantity, wherein the safety device (20) determines a safety quantity for the, in particular automatic, triggering of at least one safety measure depending on a result of the comparison.

Description

[0001] The present invention relates to a method for operating a safety device for a loading area and a safety device for a loading area.

[0002] Traffic volume is high during peak hours, especially in cities, and studies show that delivery traffic accounts for a significant portion of this. Therefore, efforts are currently underway to minimize this delivery traffic in cities. However, since a considerable number of retail outlets are located in city centers and require deliveries, these services must continue. One possible solution to this challenge is to deliver goods outside of peak hours, but this entails additional noise pollution for residents and increased personnel costs for the retail outlets (hereinafter referred to as unloading points).

[0003] While e-mobility has a positive impact on noise reduction, the second challenge remains: increased effort required at the unloading point. To address this challenge, the security aspect is particularly relevant: different suppliers gain access to the warehouse, which already contains goods, therefore personnel supervision is currently necessary.

[0004] Currently, the problem is solved by providing personnel at the unloading point. This has the disadvantage of increased personnel costs, as multiple unloading points are served and personnel must therefore be present at each one. Furthermore, off-peak deliveries often incur higher personnel costs due to, for example, night shift premiums.

[0005] Due to this problem, off-peak deliveries have not yet become widespread, despite the positive effects on traffic flow.

[0006] There are individual monitoring and security systems in place, such as electronic access control systems and camera surveillance. An electronic access control system allows a defined group of people to be granted access to the premises at a specific time using an identification feature such as a PIN code or card.

[0007] In practice, for example, time periods are defined for each specific group of people during which access is permitted. Camera surveillance, on the other hand, is either monitored live by a security service or recorded for the retrospective investigation of crimes. Besides these examples, other security systems are also in use.

[0008] In addition to the security systems, there are also systems for controlling logistics / delivery on the part of the logistics company, which has to determine the routes of the drivers and dispatch, and on the part of the unloading point, which requests the goods.

[0009] However, these systems alone are not capable of ensuring safe off-peak deliveries without personnel.

[0010] German patent application DE 10 2017 118 843 A1 discloses an autonomous delivery system that includes a security key transmitter configured to provide a security key to a server of a secure facility. Upon arrival at a security gate, a delivery vehicle can transmit a unique security key to the server of the secure facility. If the security key is valid, two-way communication is established between the server of the secure facility and the delivery vehicle. Otherwise, the on-site security service can be alerted.

[0011] US Patent 2017 / 0249581 A1 discloses a system and procedure for package delivery using a trusted alternative recipient network. The stated goal is to minimize package loss and delivery costs. The delivery driver receives real-time information on the recipient's availability on their mobile device. The system determines if the recipient is unavailable to sign for the delivery. If not, the application on the driver's mobile device automatically connects to the recipient's network and updates the route to the trusted neighbor (alternative recipient) who has indicated their availability.

[0012] German patent DE 10 2015 119 004 A1 discloses a procedure for the simplified delivery of shipments containing unpaid goods. According to the proposed procedure, an unpaid shipment can be delivered even if the recipient is absent, provided that payment for the goods can be made without the recipient's involvement, or that payment confirmation is available indicating that the goods have been paid for.

[0013] German patent DE 10 2016 220 258 A1 discloses a delivery vehicle that has a cargo space equipped with two antennas. The antennas detect transponders on cargo items, enabling a control system to monitor the current loading status of the cargo space.

[0014] From DE 10 2022 122 567 A1, a method is known for monitoring goods being transported. An initial state of the goods is recorded, and a second state is recorded after transport. Both states are transmitted to a control center, where preferably the completeness and integrity of the goods are checked, i.e., the first and second states are compared. If the two states do not match, the control center generates a notification to initiate an inspection of the goods.

[0015] A system for loading and unloading a container for goods transport is known from WO 2022 / 129 540 A1. An image or video is recorded to document the load distribution within the container, thus ensuring optimal space utilization.

[0016] From DE 10 2016 117 387 A1, a device for the secure transfer of packages at a transfer point is known. Sensors detect whether persons or objects are present at the transfer point, from which status information is generated. Based on this, a decision is made as to whether a security level has been reached and whether a transfer may subsequently take place via an activation signal, or whether a warning is issued.

[0017] German patent DE 199 11 302 A1 discloses a method for the timely monitoring of loading and unloading processes of a transport container. An identification device is attached to the cargo, which is read by a reading device during loading or unloading. This loading information is stored along with the time and location.

[0018] The present invention aims to overcome the disadvantages known from the prior art and to simplify automated or partial automation of deliveries. It also seeks to improve the security of such delivery processes.

[0019] The object of the invention is achieved by the subject matter of the independent claims. Advantageous embodiments and further developments of the invention are the subject matter of the dependent claims.

[0020] A method according to the invention is a method for operating a, in particular processor-based, safety device for a loading area, for monitoring a transfer of goods between a delivery vehicle and the loading area, wherein the safety device performs the monitoring depending on at least one monitoring parameter.

[0021] The loading area is, in particular, an area where the goods are transferred, for example, from the delivery vehicle to a recipient or a receiving area (where the goods are to be delivered), or from a sender to the delivery vehicle for the delivery of the goods. The loading area can be a loading area (e.g., a loading point) and / or an unloading area (e.g., an unloading point).

[0022] The monitoring parameter is characteristic of the monitoring data, preferably spatially resolved, acquired by means of at least one monitoring device for monitoring the loading area with regard to the handover of the goods to be delivered. The monitoring device can, for example, be an image acquisition device such as a camera. Preferably, a plurality of monitoring devices are provided for monitoring the loading area.

[0023] Preferably, the monitoring device is connected to the security device via a communication device, preferably wireless and / or wired, for data exchange and / or for storing the recorded monitoring data.

[0024] Preferably, the aforementioned loading area is located within a densely built-up area and / or a densely populated and / or an urban area, and particularly preferably within a city area and especially within a city center area.

[0025] Preferably, the loading area is a designated area for the handover of the goods, such as a loading ramp and / or a drop-off point, a drop-off locker and / or a pick-up point and / or a pick-up locker. It is conceivable that facilities for the handover of the goods are provided which are accessible only to authorized and / or authenticated persons and / or vehicles.

[0026] The delivery vehicle is preferably used to transport the goods to be handed over. It is also conceivable that the delivery vehicle (especially without further action by a driver) hands over the goods automatically and / or semi-automatically.

[0027] The term "handover of goods" refers in particular to the collection of goods and / or the delivery of goods.

[0028] In another preferred method, monitoring is at least partially automatic and preferably fully automatic.

[0029] Preferably, the monitoring data (at least partially and preferably completely) results from a recording of a delivery process of the goods to be delivered, preferably a delivery process of the delivery vehicle, by means of at least one monitoring device.

[0030] The delivery process can involve a movement and / or action linked to the delivery vehicle and / or a user of the delivery vehicle and / or the handover of the goods. For example, the movement and / or associated data (such as a timestamp) and / or a movement profile of the delivery vehicle can be recorded. It is also conceivable that an action performed by the user during the delivery process, such as a movement pattern and / or a user behavior pattern, an action to remove and / or hand over goods, and the like, is recorded. The recorded delivery process can thus be a part of a larger delivery process.

[0031] Preferably, the recorded delivery process is part of the delivery vehicle's approach to the loading area. This could be the final leg of the delivery vehicle's approach to the loading area.

[0032] Preferably, the recorded delivery process (of the goods to be handed over) does not involve an action by the delivery vehicle and / or a user of the delivery vehicle for authentication and / or authorization to hand over the cargo. Such systems may be provided as a backup. However, it is proposed to monitor general behavioral and movement patterns and other anomalies during the handover of the goods, regardless of whether authorization or authentication (with a security system) is successful or unsuccessful. This offers the advantage of creating an additional control and monitoring instance alongside existing security measures such as authorization or authentication.

[0033] Preferably, the monitoring data is derived from the recording, by means of at least one monitoring device, of an action by a user of the delivery vehicle that is not (or at least not solely) aimed at authorization and / or authentication. Therefore, the recording should not focus, or at least not exclusively focus, on actions and / or data recorded within the context of authorization and / or authentication, such as scanning an access card. Instead, the recording should focus on data that is generated and recordable from the (pure) delivery process itself, such as the approach (a related temporal dimension, a spatial dimension such as an approach route) and / or a handover modality (movement and / or behavioral data during the handover of the goods). (And at least partially record such data.)

[0034] Preferably, the monitored parameter is characteristic of a measurement triggered by a user of the delivery vehicle, indicating a characteristic of a delivery process. This measurement is preferably performed by at least one detection device. The detection can be triggered by driving into a specific area and / or approaching a predetermined area (around or to the loading area) and / or by an action (particularly by the safety device) to hand over a delivery item or an attempt to do so.

[0035] The monitoring parameter can be a parameter that is characteristic of a point in time during a delivery process, a (at least part of) delivery route, persons and / or delivery vehicles and / or aids involved in the delivery process (such as mechanical aids for transporting the goods between the loading area and the delivery vehicle, e.g., scooters; electronic aids for carrying out the handover), the person and / or their clothing of a delivering delivery vehicle, or the like.

[0036] Preferably, the user-initiated data collection is triggered by an action not specifically aimed at initiating the collection. In other words, the user unintentionally or involuntarily triggers data collection by at least one monitoring device by performing the action. For example, the user does not consciously activate a sensor to scan an identification device they present; rather, the collection is triggered by an action of the user (such as driving into a specific area), even if the user does not consciously or intentionally influence this, and especially even if the user does not perform any action specifically intended to trigger this data collection. This offers the advantage that any delivery action performed by a user and / or their delivery vehicle can trigger data collection and / or monitoring.

[0037] The triggered data capture can occur when a delivery vehicle controlled by the user enters the field of view of a camera or the area of ​​a light barrier. In an additional or alternative embodiment, however, the triggered data capture can also be targeted data capture, such as the presentation of an identification document by a user.

[0038] According to the invention, the safety device determines at least one target delivery quantity with regard to the transfer of the goods to be delivered and compares this with an actual delivery quantity determined on the basis of the at least one monitoring quantity, wherein the safety device determines a safety quantity for the, in particular automatic, triggering of at least one safety measure depending on a result of the comparison.

[0039] In particular, the operation of a system or a system is described that detects characteristics and especially anomalies during a delivery and, if these occur, alerts personnel, e.g., of a security service and / or initiates other measures.

[0040] The proposed anomaly detection system preferably draws on these different subsystems and advantageously utilizes combinatorial effects and artificial intelligence to detect anomalies and thus only tie up personnel, for example from a security service (and preferably precisely when), when an anomaly is indicated and / or detected.

[0041] This approach can also preferably achieve a reduction in congestion, especially through off-peak delivery.

[0042] Monitoring of the loading area means that the (geographical) area in which a loading, unloading, or transfer process takes place or is intended to take place is monitored, and in particular with regard to parameters or characteristics that are typical for the respective process. These can include, for example, the number of people or vehicles in this area, but also weather conditions such as temperature, precipitation, or the like. In addition, the parameter or characteristic can also include the type of delivery vehicle.

[0043] In a preferred method, a comparison and / or alignment is performed between the target delivery quantity and the actual delivery quantity. Preferably, corresponding target delivery quantities are stored in a storage device. The target delivery quantities can be derived from an expected delivery and / or from deliveries that have already taken place and / or from regular deliveries.

[0044] In another preferred method, a route is monitored. Preferably, a target route, which could potentially be taken, is known, and its adherence is monitored (for example, using GPS data) or compared with an actual route. Such a comparison can reveal, for instance, that a delivery vehicle is coming from a different location than expected or has taken a different route. On the other hand, the monitoring can also reveal that although a different route than the target route was chosen, this was done, for example, to avoid traffic jams and is therefore harmless.

[0045] Data relating to traffic conditions is also given preference in the monitoring, such as data relating to traffic jams, construction sites or accidents in the area of ​​the route.

[0046] Another preferred method takes personal data into account. This could include, for example, data characteristic of a delivery vehicle driver, such as, but not limited to, their appearance, age, gender, work attire, or habits. This allows for a comparison to determine whether an actual delivery vehicle driver matches an expected driver. In case of discrepancies, an alert can be triggered.

[0047] In another preferred method, data characteristic of a transport service (provider) is taken into account. This data is preferably selected from a group of data that includes the colors of delivery vehicles, license plate numbers of delivery vehicles, brands used by the delivery service, logos used by the delivery service, vehicle types used by the delivery service, work clothes used by the delivery service, number of people in delivery services, company data related to the delivery service, and the like.

[0048] This allows, for example, verification of whether an actual delivery vehicle matches an expected delivery vehicle.

[0049] Another preferred method defines different security levels. For example, a lower security level can be applied to the delivery of everyday goods than to the delivery of documents or cash transports. In the case of higher-value goods, for instance, multiple sensors can be monitored, different lighting can be used, or alarm thresholds can be set differently than for the delivery of lower-value goods.

[0050] Another preferred method takes into account data that is characteristic of a delivery location. For example, it can consider whether the delivery location is a residential area, a commercial area, or a mixed-use area. Furthermore, it can consider whether schools, hospitals, or similar facilities are located in the vicinity of the delivery location.

[0051] Furthermore, parking conditions in the delivery area can be taken into account, as well as, for example, limited turning options. In addition, legal framework conditions characteristic of the delivery area can be considered, such as whether the delivery area is located in a 30 km / h zone or a traffic-calmed zone.

[0052] Furthermore, a traffic situation characteristic of the delivery area can be taken into account.

[0053] Preferably, this data is also taken into account depending on the time of day and / or delivery time, i.e., depending on the traffic volume expected at a particular time of day.

[0054] The characteristic data is preferably also taken into account depending on the time of day.

[0055] In another preferred method, data characteristic of a delivery process are taken into account. These are particularly preferably selected from a group of data that are characteristic of a collection time, a collection point, a delivery time, a delivery point, a delivery time, a delivery point, a dispatch point, a delivery destination, a delivery transport, a delivery location, the goods being delivered, a transfer point, a transfer time, or a handover point.

[0056] "Delivery-relevant data" can be understood to mean a delivery destination and / or a weight and / or a delivery time and / or a (probable) arrival time of the goods to be delivered at a location (such as the central distribution station and / or a (stopping) point within the shipping area).

[0057] In another preferred method, an actual delivery quantity is determined based on at least one monitoring parameter and preferably compared with the at least one target delivery quantity. In a particularly preferred method, this transmission of the actual delivery quantity and / or the comparison with the target delivery quantity is performed continuously. It is possible for this comparison to be repeated at predetermined intervals over a predetermined period.

[0058] In another preferred method, a large number of transfers of goods by means of a delivery vehicle, which are assigned to the transfer of the goods to be transferred, are provided.

[0059] Another preferred method takes into account historical data that is associated with the handover of the goods to be delivered.

[0060] These methods can be used, for example, to teach and / or train an artificial intelligence, as detailed below.

[0061] In another preferred method, the monitoring device is selected from a group of monitoring devices comprising an image recording device, a camera, a scale, a motion sensor, a proximity sensor, an access information verification device, a QR code scanner, a barcode scanner, a device for checking a predetermined area for the entry and / or exit of an object into that predetermined area, in particular a geofencing device, a device for locating a Bluetooth-enabled terminal device, a personal identification device and the like, as well as combinations thereof.

[0062] Preferably, several of these devices are provided, and it is particularly preferred that a combination and / or linking of data recorded by these monitoring devices is carried out.

[0063] In another preferred method, the security measure is selected from a group of security measures which includes granting access, refusing access, notifying a security service, partially deactivating an alarm system, activating an alarm system, confirming the successful completion of a handover of goods, in particular a delivery, and the like, as well as combinations thereof.

[0064] Furthermore, it would also be possible to apply several of these security measures. It would also be possible to apply different security measures in a predetermined order, for example, starting with a less intrusive security measure and progressing to a more intrusive one.

[0065] In another preferred method, monitoring data is linked together to determine a target situation.

[0066] In another preferred method, monitoring data will be linked together to determine the current situation.

[0067] For example, a logical connection can be made so that a specific measure is only initiated if certain monitoring data from a first group and certain monitoring data from a second group are available. For instance, access to a delivery area could only be granted if a specific type of vehicle with a particular color or certain logos is present.

[0068] It is possible to use combinatorial aspects of the available data to determine a target situation and / or an actual situation.

[0069] In one preferred method, the monitoring data is continuously stored.

[0070] In another preferred method, artificial intelligence is used to determine a target situation and / or an actual situation and / or a comparison between a target situation and an actual situation.

[0071] Particularly preferred is AI-supported improvement of the anomaly detection system for more accurate calculation of the future target state of deliveries, especially based on the events of the current actual situation during delivery.

[0072] The proposal is to improve the process using machine learning and, in particular, to continuously improve it.

[0073] In another preferred method, a target situation and / or the data underlying this target situation is compared with an actual situation and / or the data underlying this actual situation.

[0074] This adjustment is preferably performed continuously. It is possible for such an adjustment to occur at a predetermined interval, for example, every 10 seconds. The interval can be fixed and / or adjustable by an operator. It is also conceivable that an adjustment is triggered by the detection of a deviation and / or based on a predetermined time period.

[0075] Preferably, the comparison of the at least one target delivery quantity and the determined actual delivery quantity is carried out depending on a monitoring model of machine learning, in particular a trainable model, which includes a set of parameters, in particular trainable ones, which are set to values ​​that were learned as a result of a training process, wherein the training process is based on a set of training data.

[0076] Preferably, the monitoring model of machine learning is based on an (artificial) neural network. Preferably, the neural network is a deep neural network (DNN), in which the parameterizable processing chain has multiple processing layers, and / or a so-called convolutional neural network (CNN) and / or a recurrent neural network (RNN).

[0077] Preferably, the security device comprises a plurality of data records (stored on a storage device) recorded during (previously completed) deliveries of goods. These data records were preferably recorded by, and / or derived from, at least one monitoring device and, more preferably, by a plurality of monitoring devices.

[0078] Preferably, the (especially trained) monitoring model is suitable and designed to detect deviations, anomalies, and / or patterns (compared to previous deliveries) based on the data records stored on the storage device with regard to the recorded delivery quantity and / or the monitoring data. These deviations, anomalies, and / or patterns may, in particular, be undesirable, irregular, and / or unexpected occurrences.

[0079] Preferably, the monitoring model of machine learning is / was comprehensively trained using predefined training data across a large number of training datasets, whereby the parameterizable processing chain is parameterized through training.

[0080] Supervised learning is the preferred method for training. However, it would also be possible to train the monitoring model or the artificial neural network using unsupervised learning, reinforcement learning, or stochastic learning.

[0081] The monitoring model is preferably trained on the basis of a large number of training datasets representing compliant and / or successful and / or expected delivery processes. These training datasets can consist of monitoring data and / or monitoring variables collected by at least one and / or multiple monitoring devices, or data derived therefrom.

[0082] In addition, the monitoring model may have been or be trained on the basis of a large number of training data sets, which represent a non-compliant, undesirable and / or irregular and / or unexpected (delivery) process.

[0083] It is conceivable that the monitoring model could be provided with a large number of deliveries of goods by means of a delivery vehicle, which are assigned to the delivery of the goods to be delivered, for its training and / or for the detection of an anomaly or a pattern.

[0084] Preferably, the data to be processed, in particular monitoring data and / or monitoring variables (or data derived therefrom), which were preferably determined by the at least one monitoring device, are supplied as input variables to the monitoring model or the (artificial) neural network.

[0085] Preferably, data from a planned delivery and / or supplier-related data (such as cooperating suppliers and / or delivery vehicles used by them) are also made available to the monitoring model for retrieval and / or comparison.

[0086] Preferably, the monitoring model or the artificial neural network maps the input variables to output variables as a function of a parameterizable processing chain.

[0087] It is conceivable that at least one actual delivery quantity is determined as the starting point. For example, the type of goods to be delivered, and / or a supplier, and / or an order quantity, and / or a (goods) collection date could be forecast. This could then be compared (via comparison with a target delivery quantity) to determine whether an actual delivery or collection is expected and / or planned.

[0088] It is also conceivable that the output variable is the result of comparing at least one target delivery variable with the actual delivery variable. This could indicate, for example, whether (with a given probability) an anomaly and / or a delivery process that raises safety concerns has been detected. Furthermore, the output variable could be characteristic of the type of anomaly and / or the degree of a predicted hazard. It is also conceivable that the output variable could be a warning variable used and / or usable for triggering an alarm.

[0089] The present invention further relates to a safety device for a loading area, preferably within a densely built-up area and / or an urban area and particularly preferably within a city center, for at least partially automatic, preferably fully automatic, monitoring of a transfer of goods between a delivery vehicle for transporting the goods to be transferred and the loading area, with at least one detection device for detecting at least one monitoring parameter, wherein the safety device is suitable and intended to carry out the monitoring depending on at least one monitoring parameter.

[0090] The monitoring parameter is characteristic of the monitoring data acquired by at least one monitoring device for monitoring the loading area with regard to the handover of the goods to be delivered. Preferably, the monitoring data results from a recording (of a delivery process, in particular of the delivery vehicle) by means of the at least one monitoring device.

[0091] According to the invention, the safety device comprises a determination device for determining at least one target delivery quantity with regard to the transfer of the goods to be delivered and a comparison device which compares on the basis of the at least one monitoring quantity determined, wherein the safety device is configured to determine a safety quantity for the, in particular automatic, triggering of at least one safety measure depending on a result of the comparison.

[0092] Preferably, the safety device is configured, suitable, and / or intended to execute the procedure described above, as well as all procedure steps already described above in connection with the procedure, either individually or in combination. Conversely, the procedure can be equipped with all features described within the framework of the safety device, either individually or in combination.

[0093] The present invention further relates to a safety system, in particular for monitoring a loading area, comprising a safety device as described above according to one embodiment, as well as at least one monitoring device for monitoring the loading area, and preferably a plurality of monitoring devices for monitoring the loading area. It is conceivable that the safety system includes a storage device and / or can access such a device in which the aforementioned historical data relating to the supplier and / or the delivery and / or the warehouse and / or the planned delivery and / or standard delivery vehicles are stored.

[0094] A delivery vehicle can be any type of vehicle, in particular a motor vehicle, specifically a driver-only vehicle, a semi-autonomous vehicle, an autonomous vehicle (e.g., Level 3, 4, or 5 according to SAE J3016), or a self-driving vehicle. The vehicle can be, in particular, a (motorized) road vehicle.

[0095] Level 5 autonomy refers to fully automated vehicles. The vehicle can also be a driverless transport system. It can be controlled by a driver or operate autonomously. Furthermore, the vehicle can be a road vehicle, an air taxi, another mode of transport, or a different type of vehicle, such as an aircraft, watercraft, or rail vehicle.

[0096] Preferably, the delivery vehicle is selected from a group that includes a delivery van (especially autonomous or with a driver), a truck (especially autonomous or with a driver), a cargo bike, commercial vehicles, vehicles for the (especially exclusive) transport of goods (e.g., TaaS vehicles, where TaaS is the abbreviation for "Transport as a Service"), vehicles for (especially public) passenger transport, buses, public transport vehicles, ridepooling vehicles (such as MOIA vehicles), MaaS vehicles (MaaS is the abbreviation for "Mobility as a Service"), public vehicles, (on-demand) taxis, public transport vehicles, regional transport vehicles, local transport vehicles, rail vehicles (such as subways, commuter trains, trams, light rail), long-distance (not local) transport vehicles, ridesharing vehicles, car-sharing vehicles, robotaxis and the like, as well as combinations thereof.

[0097] With regard to a delivery area and / or a loading zone, it is conceivable that this is a freely accessible loading zone, an external loading zone, a loading zone inside a building (for example, a private warehouse or a shared warehouse).

[0098] Furthermore, it is conceivable that staff may or may not be available in the loading area or at the unloading point.

[0099] Depending on these circumstances, different challenges arise, such as space requirements, applicable safety criteria, or existing knowledge, for example, where exactly delivered goods should be placed.

[0100] The present invention further relates to a computer program or computer program product, comprising program means, in particular a program code, which represents or encodes at least some of the and preferably all of the process steps of the method according to the invention and preferably one of the described preferred embodiments and is designed for execution by a processor device.

[0101] The present invention further relates to a data storage device on which at least one embodiment of the computer program according to the invention or a preferred embodiment of the computer program is stored.

[0102] The present invention further relates to a (machine-readable and / or processable by means of a processor device) data carrier signal, which is preferably characteristic of the monitoring variable described above (in particular determined by a security device described above) and / or which is preferably generated and / or is generated depending on the monitoring variable, and / or which is transmitted and / or determined and / or made available (for transmission and / or output) by the computer program described above.

[0103] The present invention has been described with regard to the transfer of cargo, particularly in the context of goods deliveries. However, the present invention is also transferable to methods and systems generally used in the logistics industry, or to methods and systems in the TaaS (Transportation as a Service) sector, especially for TaaS vehicles, and can be applied to solutions for the logistics industry or to TaaS applications. The applicant reserves the right to also claim related subject matter.

[0104] The present invention is preferably used in an urban area, in particular a city center with pedestrian zones, retail outlets and / or office buildings. Alternatively or additionally, the present invention is used in an area characterized by dense development and / or a (at least temporarily) congested traffic situation and / or in an area where only minor effects can be achieved through consolidation.

[0105] The present invention addresses the following three key challenges: There is a clear body of research on the negative impact of delivery traffic on inner-city traffic. In addition to local emissions, the parking problem (double parking) is a particular challenge. Furthermore, traffic jams are frequently caused by delivery vans that park in the second row.

[0106] The invention is preferably used for (alternative) delivery methods (especially delivery by cargo bike & micro hubs) as well as for so-called "off-peak delivery", i.e., delivery outside of peak times, especially in the B2B sector.

[0107] The goal of reducing congestion through off-peak delivery offers the advantages of increased efficiency and relieving pressure on the urban traffic network during rush hour. On the other hand, off-peak delivery also means

[0108] Further advantages and embodiments can be seen from the attached drawings:

[0109] It shows: Fig. 1 a schematic representation to illustrate the invention; Fig. 2. A representation to illustrate data to be evaluated; and Fig. 3 a description of the process of a method according to the invention.

[0110] Fig. Figure 1 shows a schematic representation illustrating a method according to the invention, preferably also taking into account the organization of deliveries in a loading zone. Reference numeral 2 denotes a delivery vehicle, here, for example, a truck. Reference numeral 1 denotes an overview 1 of the objects / facilities / systems typically and / or preferably present within a loading zone, which are shown schematically here as different blocks.

[0111] Reference numeral 3 denotes a system that takes into account the organization of deliveries in a loading zone. This can include typical delivery procedures, such as a sequence of steps leading up to the final delivery of a product.

[0112] In step 4, or in a specific configuration, a degree of automation can be considered or specified. For example, two configurations could be provided: 100% automated and semi-automated.

[0113] Reference symbol 14 generally describes the loading zone (which could, for example, be a loading zone inside a building). This could be a separate warehouse or a shared delivery area.

[0114] Different system elements 16 or 16a - 16f can be used to carry out the charging process.

[0115] For example, vehicle registration (Section 16a) can be carried out. This allows verification of whether the arriving vehicle matches the expected vehicle. This includes checking the vehicle type and / or verifying the driver. It also allows verification of whether the delivered goods match the expected goods.

[0116] In addition, status tracking (16b) regarding the delivery can be carried out at this stage. This allows verification of whether the delivery is planned, has already started, or is complete. It also allows verification of the current location of the goods.

[0117] In addition, access authorization pursuant to Article 16c can be performed. For this purpose, various data can be collected, such as license plate recognition, transponder identification, or QR code scanning. Two-factor authentication or remote unlocking can also be implemented. Furthermore, access can be granted by a security service, or access can be denied in case of discrepancies.

[0118] Reference code 16d indicates the organization of the delivery on site. Here, for example, specific time slots can be specified for certain deliveries, loading areas can be assigned, and / or the completion of a delivery can be confirmed, which can be done, for example, in a frontend for the driver.

[0119] Reference mark 16e indicates monitoring by a security service. This may involve, for example, the use of a front end for the security service. Within this context, an expected time of arrival (ETA) may be taken into account and / or camera surveillance may be used, for example, to monitor a vehicle or its driver.

[0120] Reference numeral 16f refers to the automation of monitoring and / or anomaly detection. This can be applied or activated, for example, if certain abnormal conditions occur, such as an unusually long duration of a discharge process.

[0121] Reference numeral 6 indicates organizational challenges or organizational delivery data of a delivery process, such as knowledge of correct access (or knowledge of planned security measures) for a delivery, or knowledge of exactly where the delivery goods are to be placed and / or where which delivery goods are to be placed and / or picked up and / or handed over.

[0122] Such an organization can ultimately achieve a smaller space requirement (excluding one driver), as indicated by reference numeral 18.

[0123] Fig. Figure 2 shows a diagram illustrating the different types of data that can be fed into System 20 for anomaly detection. The system can be, in particular, the (preferably purely) processor-based security device described above.

[0124] Thus, data from one or more cameras (22) is fed into the system.

[0125] Reference digit 24 identifies the data that characterizes a delivery vehicle and can be fed into system 20. This could be, for example, a recorded vehicle registration number 24a or data 24b describing the vehicle's shape (e.g., form factor), type, or color, or similar information.

[0126] In addition, position 24c of the vehicle can be taken into account. Furthermore, the weight of the delivery vehicle can also be considered.

[0127] In addition, priority is given to data 26, which describes a specific delivery process. This may include, in particular, an ETA 26a (expected time of arrival), data 26b concerning the supplier (e.g., the driver(s)), and data 26c concerning the goods to be delivered.

[0128] In addition, data concerning the warehouse (especially the warehouse to which the goods are to be delivered) can be communicated to the system.

[0129] Furthermore, mobile network data 30 or data from a mobile device are also preferentially fed into the system. This could, for example, be movement data 30a, for instance to determine whether a delivery route matches a predefined target delivery route.

[0130] In addition, BT (Bluetooth) signals or similar can also be evaluated.

[0131] Furthermore, the system also preferentially considers historical data 34 concerning the supplier, such as the reliability 34a of a particular driver in the past or the occurrence of certain events or incidents or incidences in the past 34b.

[0132] In addition, historical data 36 concerning the delivery process itself can also be taken into account, such as an (average) duration 36a of previous unloading processes.

[0133] Based on these evaluations, (especially regarding access control (arrow P in Fig. 3) Different reactions may be triggered. For example, a delivery vehicle may be denied or granted access.

[0134] Different control mechanisms can also be implemented for a loading ramp. For example, a security service can be notified, or an alarm system can be (partially) deactivated.

[0135] Several options are conceivable regarding the unloading process as well. For example, a security service could be notified.

[0136] Even after the delivery vehicle has left the delivery zone, several actions are possible. For example, a successful delivery can be confirmed. Furthermore, a previously deactivated alarm system can be reactivated. Additionally, the security service can be notified (especially automatically).

[0137] Reference numeral 10 designates a security system comprising a security device 20, which can, for example, perform anomaly detection, as well as cameras 22 and preferably further sensor devices for monitoring the loading area and storage devices for retrieving and / or storing data relating to the planned delivery and / or to a warehouse and / or to the supplier and / or to a delivery process.

[0138] Fig. Section 3 describes, by way of example, the sequence of steps of a process according to the invention.

[0139] The anomaly detection system 20 is connected, particularly via APIs (Application Programming Interfaces), to various input systems 21, such as data from the ERP system, notifications from the supplier regarding the time of delivery, or historical data about the supplier. One aspect here is the supplier evaluation based on reliability and past events.

[0140] If there is existing experience regarding the (un)reliability of the supplier, the thresholds for triggering an event will be affected. This can happen both positively and negatively. Automated data collection may be supplemented by manual input to achieve a defined minimum target state if the automatically collected data is insufficient.

[0141] During delivery, the target situation 42 – preferably continuously – is compared with the actual situation 44 (double arrow 46), and appropriate action is taken. Existing safety systems 20 are preferably used and evaluated. Reference numeral 40 indicates a corresponding comparison device.

[0142] The current situation can also be analyzed using the data provided by System 20.

[0143] Some examples of a corresponding reaction: a vehicle arrives at the expected time, but it differs in form factor (detection via camera, van instead of truck) or license plate from the calculated target scenario.

[0144] A corresponding system response E could be the refusal of access and connection to the security service, which, after manual verification, may reject the supplier or grant access.

[0145] In another scenario, deviations in the duration of the unloading process, the vehicle's position within the building (controlling the correct loading ramp), or its positioning within the warehouse (movement detected by cameras or Bluetooth) would be considered. In these cases, System 20 interacts with the individual security systems (e.g., the access control system) for anomaly detection.

[0146] In addition, the weight of the goods can also be taken into account. For example, an anomaly can be detected if a measured weight differs significantly from the target weight of the goods (e.g., according to the delivery note or determined from the nature of the goods).

[0147] Different front ends inform different stakeholders. The front end for drivers provides information about time slots, loading area assignments, and delivery confirmation.

[0148] The security service's front end primarily displays all relevant details about the upcoming delivery (e.g., expected vehicle, ETA, advance warning of the delivery) to enable appropriate responses if necessary. The customer's front end provides status tracking for the entire delivery (e.g., Planned, Started, Completed, ETA; overview of deliveries). A high degree of automation ensures that personnel costs, for example, on the security service's side, are reduced.

[0149] The applicant reserves the right to claim all features disclosed in the application documents as essential to the invention, provided they are novel individually or in combination compared to the prior art. It is further noted that the individual figures also describe features which may be advantageous on their own. A person skilled in the art will immediately recognize that a particular feature described in a figure may be advantageous even without incorporating other features from that figure. Furthermore, a person skilled in the art will recognize that advantages may also arise from a combination of several features shown in individual or different figures. Reference symbol list 1 Overview of the loading zone 2. Delivery vehicle 3. System for organizing deliveries with loading zone 4. Degree of automation 6. Organizational delivery data 10 Security system 14 loading zones 16, 16a - 16f System elements for carrying out the charging process 18 Advantage: smaller space requirement 20 Safety device 21 Input Systems 22 camera(s) 24 Data identifying a delivery vehicle 25 AI-supported learning 24a - 24c Examples of data 24 26 planned delivery dates 26a - 26c Examples of data 26 28 Data concerning the warehouse 28a Designated loading location 30 data mobile phone 30a, 30b Examples of data 30 34 Historical Data Supplier 34a, 34b Examples of data 34 36 Historical Data Delivery 36a Data unloading process 40 Comparison device for comparing the current situation with the target situation 42 Target situation 44 Current situation 46 Double Arrow E Alarm Security Service P arrow

Claims

[1] Method for operating a security device (20) for a loading area (4), preferably within a densely built-up area and / or an urban area and particularly preferably within a city center, for at least partially automatic, preferably fully automatic, monitoring of a transfer of goods between a delivery vehicle (2) for transporting the goods to be transferred and the loading area (4), wherein the security device (20) performs the monitoring depending on at least one monitoring parameter, wherein the monitoring parameter is characteristic of monitoring data recorded by means of at least one monitoring device (22) for monitoring the loading area (4) with regard to the transfer of the goods to be transferred, wherein the monitoring data results from a recording of a delivery process of the goods to be transferred by means of the at least one monitoring device (22), characterized by, that the safety device (20) determines at least one target delivery quantity with regard to the transfer of the goods to be transferred and compares it with an actual delivery quantity determined on the basis of the at least one monitoring quantity, wherein the safety device (20) determines a safety quantity for the, in particular automatic, triggering of at least one safety measure depending on a result of the comparison. [2] Method according to claim 1, characterized by , that on the basis of at least one monitoring variable an actual delivery variable is determined and preferably compared with the at least one target delivery variable, wherein preferably this transmission of the actual delivery variable and / or the comparison with the target delivery variable takes place continuously. [3] Method according to any of the preceding claims, characterized by, that a large number of deliveries of goods by means of a delivery vehicle, which are assigned to the delivery of the goods to be delivered, are provided and / or historical data are taken into account which are assigned to the delivery of the goods to be delivered. [4] Method according to any one of the preceding claims, characterized by , that the monitoring device (22) is selected from a group of monitoring devices comprising an image recording device, a camera, a scale, a motion sensor, a proximity sensor, an access information verification device, a device for checking a specified area for the entry and / or exit of an object into that specified area, in particular a geofencing device, a device for locating a Bluetooth-enabled terminal device, a personal identification device and the like, as well as combinations thereof. [5] Method according to any one of the preceding claims, characterized by , that the security measure is selected from a group of security measures which includes granting access, denying access, notifying a security service, partially deactivating an alarm system, activating an alarm system, confirming the successful completion of a handover of goods, in particular a delivery, and the like, as well as combinations thereof. [6] Method according to any of the preceding claims, characterized by , that monitoring data is linked together to determine a target situation and / or monitoring data is linked together to determine an actual situation. [7] Method according to any of the preceding claims, characterized by that artificial intelligence is used to determine a target situation and / or an actual situation. [8] Method according to any of the preceding claims, characterized by , that a comparison of a target situation and / or the data underlying this target situation with an actual situation and / or the data underlying this actual situation takes place, preferably with this comparison taking place continuously. [9] A safety device (20) for a loading area (4), preferably within a densely built-up area and / or an urban area and particularly preferably within a city center, for at least partially automatic, preferably fully automatic, monitoring of the transfer of goods between a delivery vehicle (2) for transporting the goods to be transferred and the loading area (4), comprising at least one detection device for recording at least one monitoring parameter, wherein the safety device (20) is suitable and intended to carry out the monitoring depending on at least one monitoring parameter, wherein the monitoring parameter is characteristic of the monitoring data recorded by means of at least one monitoring device (22) for monitoring the loading area (4) with regard to the transfer of the goods to be transferred.wherein the monitoring data result from a recording of a delivery process of the goods to be delivered by means of at least one monitoring device (22), characterized by , that the safety device (20) has a determination device for determining at least one target delivery quantity with regard to the handover of the goods to be handed over and a comparison device which compares on the basis of the at least one monitoring quantity determined, wherein the safety device (20) is configured to determine a safety quantity for the, in particular automatic, triggering of at least one safety measure depending on a result of the comparison. [10] Safety system (20) comprising a safety device (20) according to the preceding claim and at least one monitoring device (22) for monitoring the loading area (4).

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