System and method for remote parcel collection and computer program product thereof

Abstract

A system and a method for remote parcel collection and computer program product thereof are provided. A multi-channel notification module is configured to send a notification to a user device based on a doorbell triggered message from a doorbell. A video monitoring module is configured to control a camera for real-time image capture. A face recognition module is configured to perform a face recognition on the real-time image to produce a face recognition result. A multimodal biometric module is configured to biometrically recognize a biometric information from a biosensor device to generate a biometric result. A door lock control module is configured to control a door lock based on a command from the user device or the facial recognition result and / or the biometric result. A fence message module is configured to generate a fencing area detection result based on a fence trigger message from an electronic fence, whereby the multi-channel notification module notifies the user device based on the fence area detection result.

Description

Remote parcel collection system, method and its computer program product This case concerns remote parcel collection integration technology, specifically, a remote parcel collection system, method, and computer program product utilizing cameras. The development of e-commerce has made online shopping a primary way to purchase goods and services. However, when consumers are not at home and cannot receive their packages in time, the packages may be at risk of being stolen, lost, or affected by weather. Existing solutions include several options, but each has its shortcomings. First, entrusting a manager to collect packages relies on the manager's cooperation, but the manager may be too busy or unavailable to handle packages promptly, potentially raising privacy and security concerns. Second, using community parcel lockers requires dedicated lockers, but their limited capacity may lead to overcrowding. Third, smart parcel lockers require consumers to pick up their packages at designated locations, which is inconvenient, costly to set up, and space-consuming, making them less than ideal for small communities or individual residences. In addition, most parcel collection systems on the market currently lack real-time monitoring and remote control functions, and are difficult to operate effectively when unattended, increasing the risk of parcels being misdelivered or lost during delivery. Therefore, it is clear that there is a need to improve the integration technology for remote parcel collection. To address the aforementioned and other issues, this case discloses a remote parcel collection system, method, and its computer program product. A remote parcel collection system includes: a multi-channel notification module, which sends notifications to a user terminal device based on doorbell trigger messages transmitted by a doorbell connected to the remote parcel collection system, and allows the user terminal device to set various communication methods and communication sequences; an image monitoring module, which controls a camera connected to the remote parcel collection system to acquire real-time images; a facial recognition module, which performs facial recognition on the real-time images acquired by the image monitoring module to generate facial recognition results; and a multimodal biometric module, which identifies the facial features of the person connected to the remote parcel collection system. The system uses biometric information from object sensors for biometric identification to generate biometric results; the door lock control module controls the door locks connected to the remote parcel collection system based on commands from the user terminal device, the facial recognition results from the facial recognition module, and / or the biometric results from the multimodal biometric module; and the fence message module generates fence area detection results based on fence trigger messages from the electronic fence connected to the remote parcel collection system, so that the multi-channel notification module can notify the user terminal device based on the fence area detection results. A remote parcel collection method, executed by a remote parcel collection system, includes: notifying a user terminal device based on a doorbell trigger message transmitted from a doorbell communicatively connected to the remote parcel collection system; controlling a camera communicatively connected to the remote parcel collection system to acquire real-time images; performing facial recognition on the real-time images to generate a facial recognition result; performing biometric identification on biometric information transmitted from a biometric sensor communicatively connected to the remote parcel collection system to generate a biometric identification result; controlling a door lock communicatively connected to the remote parcel collection system based on a command from the user terminal device or the facial recognition result and the biometric identification result; and generating a fence area detection result based on a fence trigger message transmitted from an electronic fence communicatively connected to the remote parcel collection system, and notifying the user terminal device based on the fence area detection result. The remote parcel collection system and method further include performing behavior recognition and anomaly detection on the real-time image, and transmitting the behavior recognition and anomaly detection results to the user terminal device. The remote parcel collection system and method further include performing scene recognition on environmental perception information transmitted by an environmental perception device that is communicatively connected to the remote parcel collection system, so as to generate a scene recognition result, wherein the activation of the biosensor is controlled according to the scene recognition result. The remote parcel collection system and method further include enabling the remote parcel collection system to communicate with the delivery platform to obtain the predicted delivery time, thereby enabling the fence message module to generate a fence area detection result based on the fence trigger message and the predicted delivery time; and scoring based on the fence area detection result to transmit the scoring result to the deliveryman evaluation platform. A computer program product, loaded onto a computer to execute the aforementioned remote parcel collection method. Based on the above, this case utilizes cameras, biometric sensors, environmental sensing devices, and electronic fences on the user end, combined with remote video monitoring and door lock control mechanisms on the server end. It employs AI facial recognition technology, AI behavior recognition and anomaly detection technology, AI integrated environmental perception technology, and AI electronic fence technology to trigger real-time video functionality during the delivery process. This leverages facial recognition results, biometric results, behavior recognition and anomaly detection results, scene recognition results, and fence area detection results to enhance the delivery person's identity verification, thereby achieving convenience when no one is home to pick up the goods remotely, while ensuring the security and credibility of the delivery process. 11: Doorbell 12: Camera 13: Biosensor Device 14: Environmental sensing device 15: Door Lock 16: Electronic Fence 2: Remote parcel collection system 20: Multi-channel notification module 21: Video surveillance module 22: Facial Recognition Module 23: Multimodal biometric module 24: Integrating the environmental perception module 25: Door lock control module 26: Fence Message Module 27: Behavior Recognition and Anomaly Detection Module 28: Delivery Forecasting Module 29: Rating Module 3: User terminal device 30: Remote Parcel Collection App 4: Delivery platform 5: Deliveryman review platform S21~S29, S31~S32: Steps Figure 1 is a schematic diagram of the remote parcel collection system in this case. Figure 2 is a flowchart of the remote parcel collection method in this case. The following specific embodiments illustrate the implementation of this invention. Those skilled in the art can easily understand the other advantages and effects of this invention from the content disclosed herein. The structures, ratios, sizes, etc., illustrated in the accompanying drawings are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed herein, and are not intended to limit the implementation conditions of this invention. Therefore, any modifications, changes, or adjustments, without affecting the effects and purposes achieved by this invention, should still fall within the scope of the technical content disclosed herein. The terms “comprising,” “including,” “having,” “containing,” or any other variation thereof, as used herein, are intended to cover non-exclusive inclusion. Unless otherwise stated, singular terms such as “a,” “an,” and “the” also apply to plural terms, while terms such as “or,” “and / or,” etc., are used interchangeably. Please refer to Figure 1, which illustrates the schematic architecture of the remote parcel collection system in this case. The remote parcel collection system 2 includes a multi-channel notification module 20, an image monitoring module 21, a facial recognition module 22, a multimodal biometric module 23, an integrated environmental perception module 24, a door lock control module 25, a fence information module 26, a behavior recognition and anomaly detection module 27, an arrival prediction module 28, and a scoring module 29. In addition, the remote parcel collection system 2 communicates with the doorbell 11, camera 12, bio-sensor 13, environmental sensor 14, door lock 15, and electronic fence 16 installed at the user's home, and also communicates with the delivery platform 4, the deliveryman evaluation platform 5, and the user terminal device 3 carrying the remote parcel collection App 30. The multi-channel notification module 20 sends notifications to the user terminal device 3 based on doorbell trigger messages received when doorbell 11 is triggered, door lock unlock messages received when door lock 15 is unlocked, or fence trigger messages received when electronic fence 16 is triggered. This allows the user terminal device 3 to respond to the remote parcel collection system 2 via the remote parcel collection app 30, thereby unlocking door lock 15 or performing other controls. Furthermore, the multi-channel notification module 20 allows the user terminal device 3 to configure various communication methods and communication sequences. In one embodiment, the multi-channel notification module 20 utilizes Robotic Process Automation (RPA) technology. For example, when a user's package arrives at the delivery point, the logistics system automatically generates a notification event. The RPA robot then retrieves package data from the logistics system (such as package number, package name, delivery time, delivery point address, etc.) and formats the data into message content suitable for notifying the user. Then, the RPA sends the preset communication content to the user by calling communication tool APIs (such as Line Notify API, WhatsApp Business API, Telegram Bot API). This combines multiple communication tools such as Line Notify, WhatsApp, and Telegram to provide intelligent notifications in addition to the remote package collection app 30. The video monitoring module 21 is used to control the camera 12 to acquire real-time images, and to store the real-time images in a database, such as MongoDB, thereby obtaining low latency and high reliability data processing performance. In one embodiment, when the remote parcel collection system 2 receives a doorbell trigger message from the doorbell 11, a door lock unlock message from the door lock 15, or a fence trigger message from the electronic fence 16, the video monitoring module 21 controls the camera 12 to start recording, capturing the entire process of parcel delivery. The real-time video received by the video monitoring module 21 from the camera 12 can be transmitted to the user terminal device 3 via a multi-channel notification module 20. Alternatively, the camera 12 can also be designed to be controlled by the doorbell 11, door lock 15, or electronic fence 16, which are also located at the doorway, to start recording. The face recognition module 22 is used to perform face recognition on the real-time images acquired by the image monitoring module 21 to generate face recognition results. In one embodiment, the face recognition module 22 employs an open-source computer vision library (OpenCV), for example, combining the LBPH (Local Binary Patterns Histograms) algorithm to perform deliveryman face recognition through model training and real-time comparison. The face recognition module 22 uses OpenCV's Haar Cascade method to detect facial regions in images, performs grayscale processing on the faces, and trains a deliveryman face model (e.g., face.yml) using LBPHFaceRecognizer, recording the feature vector and corresponding ID of each deliveryman. In real-time recognition, the face recognition module 22 acquires images from the image monitoring module 21, performs face comparison using a trained model, and returns the matching ID and confidence index. The lower the confidence index, the higher the accuracy of the match. When the index is lower than the system's preset judgment standard, the recognition is confirmed to be successful. The resulting face recognition results can be used by the door lock control module 25 to further control the door lock 15, and can be sent back to the remote parcel collection App 30 of the user terminal device 3 by the multi-channel notification module 20. The multimodal biometric module 23 is used to perform biometric identification on the biometric information transmitted by the biometric sensor 13, such as multi-level verification of various biometric features such as voiceprint recognition, iris recognition, and fingerprint recognition, so as to generate biometric identification results. In one embodiment, when the face recognition module 22 generates a "face recognition successful" result, the multimodal biometric module 23 can be activated to perform other biometric recognitions. The resulting biometric results can be used by the door lock control module 25 to further control the door lock 15, and can be transmitted back to the remote package collection App 30 of the user terminal device 3 via multiple notification modules 20. Accordingly, even if the face recognition module 22 cannot recognize the face due to a blurred or obscured facial image, verification can still be provided using other biometric features such as voiceprint recognition. In addition to the facial recognition and biometrics used for delivery personnel, the remote parcel collection system 2 can also use Authentication (Oauth, Basic, JWT, token) technology for recipients (such as the remote parcel collection app 30) to ensure that only authorized personnel can open the door through the app. The integrated environmental perception module 24 is used to perform scene recognition on the environmental perception information transmitted by the environmental perception device 14 to generate scene recognition results. The multimodal biometric module 23 controls the biometric sensing device 13 to start according to the scene recognition results. In one embodiment, the integrated environmental perception module 24 includes the perception of conditions such as ambient audio, light, and weather to automatically identify whether the current scene meets normal delivery conditions. For example, at night or in a dark environment, the system will activate a stricter security mode, adding additional verification steps, such as activating the multimodal biometric module 23 to require the delivery person to perform voiceprint verification or use dual biometrics. The door lock control module 25 controls the door lock 15 according to the command of the user terminal device 3, or the facial recognition result of the facial recognition module 22 and the biometric result of the multimodal biometric module 23. In one embodiment, the remote parcel collection App 30 of the user terminal device 3 sends a request through the Representational State Transfer (REST) ​​Application Programming Interface (API) and transmits it to the remote parcel collection system 2 via the Hypertext Transfer Protocol (HTTP). The door lock control module 25 then uses this request to maintain a connection with the door lock 15 via Message Queuing Telemetry Transport (MQTT) to achieve intelligent unlocking and locking. The fence message module 26 generates a fence area detection result based on the fence trigger message transmitted by the electronic fence 16, so that the multi-channel notification module 20 can notify the user terminal device 3 based on the fence area detection result. In one embodiment, the electronic fence 16 has a detection area and a detection time to ensure that the delivery person can only unload goods in the detection area and / or the detection time. If the delivery person exceeds the detection area and / or the detection time, the multi-channel notification module 20 sends a notification to the user terminal device 3. The behavior recognition and anomaly detection module 27 is used to perform behavior recognition and anomaly detection on the real-time images acquired by the video surveillance module 21, so as to generate behavior recognition and anomaly detection results and then transmit them to the user terminal device 3. In one embodiment, deep learning models (such as I3D or YOLO combined with OpenPose) are used for analysis. I3D captures both spatial and temporal features, making it suitable for analyzing complex continuous actions, while YOLO quickly detects target locations. Combined with OpenPose, key points of the human skeleton can be extracted, enabling efficient and accurate identification of static and dynamic behaviors. This is suitable for analyzing the behavioral patterns of delivery personnel or residents, such as their movement trajectories, standing postures, and actions of opening delivery boxes within the detection area of ​​the electronic fence 16. The behavior recognition and anomaly detection module 27 can be trained on images using AI models (such as LSTM combined with CNN or Transformer-based models) to learn typical operational behavior patterns. Once abnormal actions that do not conform to expected behavior (such as prolonged lingering or suspicious behavior) are detected, the multi-channel notification module 20 will be activated to alert residents or managers, proactively detecting potential security threats. The delivery prediction module 28 communicates with the delivery platform 4 to obtain the predicted delivery time. The fence message module 26 generates a fence area detection result based on the fence trigger message and the predicted delivery time, thereby generating a fence area detection result for whether the goods have entered the detection area within the predicted delivery time. In one embodiment, the delivery prediction module 28 uses AI technology to predict the arrival time of goods. The module analyzes logistics data (such as shipping time, delivery route, and goods location), environmental data (such as weather conditions and traffic conditions), and historical data (such as average delivery time for the same location and time period). Through data cleaning and feature engineering, it extracts key factors affecting delivery time and inputs the processed data into a deep learning model. The model can be an LSTM (Long Short-Term Memory network for processing time series data) or a Transformer (capturing the correlation and nonlinear relationship between multidimensional data). Through supervised learning, an accurate delivery time prediction model is established to help residents arrange their delivery time in advance. The scoring module 29 is connected to the deliveryman evaluation platform 5. The scoring module 29 performs intelligent scoring based on the fence area detection results of the fence information module 26. The intelligent scoring refers to the process of automatically analyzing various data in the delivery process using AI technology, including the timeliness of delivery, package integrity, and whether it conforms to the standard operation, and generating dynamic scores based on the data, so as to transmit the scoring results to the deliveryman evaluation platform 5. In one embodiment, each delivery process or result is linked to a delivery personnel rating mechanism. If abnormal behavior is detected (such as damaged packages or failure to deliver on time), the rating module 29 can lower the rating and notify the delivery personnel evaluation platform 5. It should be noted that the remote parcel collection system 2 can be executed by a cloud server, and each module therein can be software, hardware, or firmware; if it is hardware, it can be a processing unit, processor, or computer host with data processing and computing capabilities; if it is software or firmware, it can include instructions that can be executed by a processing unit, processor, computer, or computer host, and can be installed on the same hardware device or distributed across different multiple hardware devices. Please refer to Figure 2 to illustrate the process architecture of the remote parcel collection method in this case. The remote parcel collection method can be executed by the remote parcel collection system shown in Figure 1, including steps S21 to S29 and steps S31 to S32. In step S21, the remote parcel collection system receives a doorbell trigger message from the user's home doorbell. Then proceed to step S22. In step S22, the remote parcel collection system controls the camera at the user's home (or the camera itself) to acquire real-time images. Then proceed to steps S23 and S31. In step S31, the remote parcel collection system transmits real-time video to the user terminal device. Then proceed to step S32. In step S32, the remote parcel collection system receives commands from the user terminal device. Then proceed to step S27. In step S23, the remote parcel collection system performs facial recognition on the real-time image to generate a facial recognition result. Then proceed to step S24. In step S24, the remote parcel collection system performs behavior recognition and anomaly detection on the real-time image, and transmits the behavior recognition and anomaly detection results to the user terminal device 3. Then proceed to step S25. In step S25, the remote parcel collection system performs biometric identification on the biometric information from the biometric sensor at the user's home to generate a biometric identification result. Then proceed to step S26. In one embodiment, biometrics such as voiceprint recognition, iris recognition, and fingerprint recognition are used for multi-level verification. In step S26, the remote parcel collection system performs scene recognition on the environmental sensing information from the user's home environment sensing device to generate a scene recognition result. Then proceed to step S27. In one embodiment, environmental perception includes sensing conditions such as ambient audio, light, and weather to automatically identify whether the current scene meets normal delivery conditions. In step S27, the remote parcel collection system controls the door lock based on commands from the user's device, or facial recognition results and / or biometric results. Then proceed to step S28. In step S28, the remote parcel collection system receives a fence trigger message from the electronic fence at the user's home to generate a fence area detection result. Then proceed to step S29. In step S29, the remote parcel collection system notifies the user device based on the facial recognition results, behavior recognition and anomaly detection results, biometric recognition results, scene recognition results, and fence triggering information. Furthermore, this application provides a computer program product that executes the aforementioned method after being loaded onto a computer. The computer program (product) can be stored on a recording medium or directly transmitted and provided over a network; that is, the computer program (product) is anything containing a computer-readable program and is not limited to any particular external form. The computer includes, but is not limited to, electronic devices with a processor. Furthermore, this application also provides a computer-readable recording medium, which is used in a computing device or computer having a processor and / or memory. The computer-readable recording medium stores instructions, and the computing device or computer can execute the computer-readable recording medium through the processor and / or memory to perform the aforementioned methods and / or content when executing the computer-readable recording medium. The computer-readable recording medium (e.g., hard disk, floppy disk, optical disk, USB flash drive) stores the computer program (product). In one embodiment, the computer-readable recording medium is a non-transitory computer-readable recording storage medium. In summary, this case provides a remote parcel collection technology with the following advantages: 1. Reduced Logistics Costs: Remote parcel collection technology allows delivery personnel to store parcels directly in designated secure areas, eliminating the need for multiple delivery attempts to the recipient's door, thus reducing duplicate deliveries caused by recipients not being home. Furthermore, combined with AI-powered delivery prediction technology, residents can schedule delivery times in advance, avoiding delays and ineffective deliveries. This not only improves delivery efficiency, especially in congested areas, but also significantly reduces fuel and labor costs for logistics companies. 2. Improved Community Management Efficiency: The system's intelligent notification and parcel collection technology reduce the need for administrators to assist residents with parcel collection in their daily work. The automated operation of the parcel locker system allows administrators to focus their energy on other important tasks, such as security patrols, facility maintenance, or daily resident services. This not only improves the efficiency of community management but also enhances residents' quality of life, making management work easier and more efficient. 3. Enhanced Security: The system integrates high-resolution surveillance cameras and multimodal biometric technologies (such as facial recognition, voiceprint, and fingerprint recognition). Each time a package is delivered, the camera automatically records the video and instantly transmits it to the cloud for secure storage, ensuring the delivery process is traceable. Furthermore, AI facial recognition combined with other biometric identification methods accurately verifies the delivery person's identity, preventing unauthorized unlocking. Moreover, the electronic fence function further ensures that delivery personnel can only operate within authorized areas, preventing packages from being misdelivered or improperly placed, thus significantly reducing the risk of package loss or theft. 4. Improve overall user experience: The system simplifies the remote package collection process. The recipient only needs to operate the door lock through the remote app. If the recipient does not notice the notification, the system will trigger the camera to automatically perform AI facial recognition to confirm the identity and perform remote operations on behalf of the recipient, increasing the convenience of the overall process. The above embodiments are merely illustrative of the effects of this application and are not intended to limit the scope of this application. Any person skilled in the art may modify and alter the above embodiments without departing from the spirit and scope of this application. Therefore, the scope of protection of this application should be as set forth in the following patent application claims. 11: Doorbell 12: Camera 13: Biosensor Device 14: Environmental sensing device 15: Door Lock 16: Electronic Fence 2: Remote parcel collection system 20: Multi-channel notification module 21: Video surveillance module 22: Facial Recognition Module 23: Multimodal biometric module 24: Integrating the environmental perception module 25: Door lock control module 26: Fence Message Module 27: Behavior Recognition and Anomaly Detection Module 28: Delivery Forecasting Module 29: Rating Module 3: User terminal device 30: Remote Parcel Collection App 4: Delivery platform 5: Deliveryman review platform

Claims

1. A remote parcel collection system includes: The multi-channel notification module sends a notification to the user terminal device based on the doorbell trigger message transmitted by the doorbell connected to the remote parcel collection system, and allows the user terminal device to set various communication methods and communication sequences. The video surveillance module controls the camera that communicates with the remote parcel collection system to obtain real-time images; The facial recognition module performs facial recognition on the real-time images acquired by the video monitoring module to generate facial recognition results. The multimodal biometric module performs biometric identification on the biometric information transmitted by the biometric sensor connected to the remote parcel collection system to generate a biometric identification result. The door lock control module controls the door lock connected to the remote parcel collection system based on commands from the user terminal device, facial recognition results from the facial recognition module, and / or biometric results from the multimodal biometric module; and The fence information module generates fence area detection results based on fence trigger messages transmitted from the electronic fence that is connected to the remote parcel collection system. This results are then used by the multi-channel notification module to notify the user device. The remote parcel collection system described in claim 1 further includes a behavior recognition and anomaly detection module, which performs behavior recognition and anomaly detection on the real-time images acquired by the image monitoring module, and transmits the behavior recognition and anomaly detection results to the user terminal device. The remote parcel collection system described in claim 1 further includes an integrated environmental perception module, which performs scene recognition on environmental perception information transmitted by an environmental perception device that is communicatively connected to the remote parcel collection system, so as to generate scene recognition results. The remote parcel collection system described in Request 1 further includes an arrival prediction module, which communicates with the delivery platform to obtain the predicted arrival time, thereby enabling the fence information module to generate fence area detection results based on the fence trigger message and the predicted arrival time. The remote parcel collection system described in claim 4 further includes a rating module, which is connected to the deliveryman evaluation platform. The scoring module scores the area based on the detection results and transmits the scores to the deliveryman evaluation platform. A method for remote parcel collection, executed by a remote parcel collection system, includes: The system sends a notification to the user device based on the doorbell trigger message transmitted by the doorbell that is connected to the remote parcel collection system. Control the camera that communicates with the remote parcel collection system to obtain real-time images; Facial recognition is performed on the real-time image to generate facial recognition results; Biometric identification is performed on the biometric information transmitted by the biometric sensor connected to the remote parcel collection system to generate a biometric identification result. Based on commands from the user terminal device or the facial recognition and biometric results, the system controls the door lock connected to the remote parcel collection system; and Based on the fence trigger message transmitted by the electronic fence that is connected to the remote parcel collection system, a fence area detection result is generated, and the user terminal device is notified based on the fence area detection result. The remote parcel collection method described in Request 6 further includes: Behavior recognition and anomaly detection are performed on the real-time video, and the results of behavior recognition and anomaly detection are transmitted to the user terminal device. The remote parcel collection method described in Request 6 further includes: The environmental perception information transmitted by the environmental perception device that is connected to the remote parcel collection system is used to perform scene recognition to generate scene recognition results. The remote parcel collection method described in Request 6 further includes: The remote parcel collection system is connected to the delivery platform to obtain the predicted delivery time. This allows the fence information module to generate fence area detection results based on the fence trigger message and the predicted delivery time. The system then scores the fence area based on the detection results and transmits the scores to the deliveryman evaluation platform. A computer program product, loaded onto a computer to execute the remote parcel collection method as described in any one of claims 6 to 9.

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