A method and system for building trustworthy operational evidence in automated community emergency services

Abstract

The application discloses a kind of in automated community emergency service Method and system for building credible operation evidence.The method is synchronized with entity service process, and environment evidence is collected by automatically responding to operation event, and after privacy processing, it is bound with business identification, then tamper-proof protection such as blockchain storage, digital signature, trusted timestamp is applied, and finally, independently verifiable evidence unit is formed and chain storage.System corresponds to include event listening, evidence collection, processing, trust enhancement and storage units.The application solves the core pain points of untrusted process, invalid evidence and non-compliant records in automated services, and provides solid legal and technical support for high-trust scenarios such as smart aging and instant logistics.

Description

Technical Field

[0001] This invention relates to the fields of Internet of Things, information security and data evidence storage technology. Specifically, it relates to a method and system that is deeply coupled with unmanned community emergency service processes to automatically generate, process and store legally valid operational evidence. Background Technology

[0002] Currently, automated equipment such as drones and unmanned vehicles are being used in community emergency services (such as emergency medicine delivery). While this has improved efficiency, issues regarding the reliable recording and compliance of the service process have become prominent. Existing technological solutions typically rely on scattered system logs or independently operating surveillance videos. These records are easily tampered with, difficult to link to specific service orders, and pose legal risks of infringing on public privacy. When service disputes, property damage, or safety incidents occur, it is difficult to provide complete, reliable, and compliant legal evidence, leading to difficulties in determining liability and hindering the large-scale and standardized development of this service. Summary of the Invention

[0003] The technical problems this invention aims to solve are as follows: Solving the problem of evidence credibility: How to establish a fully automated, tamper-proof, and independently verifiable chain of evidence for automated, multi-stage community emergency services. Solving the problem of privacy compliance: How to automatically eliminate the collection and storage of sensitive personal information of irrelevant third parties (such as facial features and license plates) while recording the entire process (especially audio and video recordings) to meet the mandatory requirements of laws and regulations such as the Personal Information Protection Law. Solving the problem of evidence association and management: How to uniquely, efficiently, and systematically associate and manage the massive amounts of evidence generated across different devices and stages with specific service orders and logistics documents.

[0004] Technical Solution. To solve the above-mentioned technical problems, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for constructing credible operational evidence in automated community emergency services, characterized by including an evidence chain construction process executed synchronously with the service process, the process including: S1. Event Response and Collection: In response to at least one predefined operational event occurring in the service process, automatically collect environmental state evidence representing the occurrence of the event; S2. Association and Binding: Associate and bind the collected environmental state evidence with a specific service business identifier that triggered the evidence collection; S3. Trust Enhancement: Apply anti-tampering and time credibility guarantees to the evidence data after association and binding; S4. Evidence Chaining: Persistently store the evidence data after trust enhancement processing to form a service operation evidence unit that can be independently verified afterward; Multiple evidence units related to the same service order are logically associated in chronological order to form a complete service operation evidence chain. It should be noted that the core purpose of "applying anti-tampering and time credibility guarantees" in the present invention is to technically ensure that the evidence data has not been tampered with since its generation and can provide credible proof of its generation time. Any technical means capable of achieving the above objectives, such as, but not limited to, the specific methods listed in the claims and embodiments, fall within the scope of the "trust enhancement" described in this invention. Secondly, a trusted operational evidence construction system for implementing the above method is provided, characterized by comprising: an event monitoring unit for listening to and capturing predefined operational events published in the service process; an evidence collection unit connected to the event monitoring unit for collecting environmental state evidence in response to event triggering; an evidence processing unit for associating the evidence data submitted by the evidence collection unit with the corresponding service business identifier and performing privacy compliance processing; a trust enhancement unit for applying anti-tampering and time-based trustworthiness guarantees to the data output by the evidence processing unit; and an evidence storage unit for persistently storing the final evidence data processed by the trust enhancement unit and providing indexing and query services.

[0005] Beneficial Effects. Compared with existing technologies, this invention has the following beneficial effects: 1. Constructs a judicially credible closed loop: Through the process of "event triggering - evidence fixation - trust enhancement," the generated evidence units possess tamper-proof and verifiable characteristics, forming an evidence chain that complies with the requirements of the Electronic Signature Law, greatly enhancing the legal credibility and dispute resolution capabilities of the service. 2. Achieves proactive privacy compliance: By embedding privacy desensitization processing as a necessary step in evidence generation, compliance risks are eliminated from the source, enabling large-scale, continuous service process recording to be implemented within the legal framework. 3. Constructs a high-cost technical and process barrier to circumvent it: This invention protects the systematic method and architecture of "evidence chain construction," rather than a single algorithm. Competitors must completely reproduce this complex system and process to achieve the same effect, making circumvention extremely difficult and costly. 4. Provides precise risk management tools: Specifically targeting accidents and abnormal behaviors during transportation, the system can automatically capture and fix key evidence, providing indisputable original evidence for operators to make insurance claims and determine accident liability.

[0006] Brief Description of the Drawings. The present invention will be further described below with reference to the accompanying drawings. It should be understood that these drawings are merely illustrative and should not be construed as limiting the scope of protection of the present invention.

[0007] Figure 1 This is a schematic diagram of the logical architecture and data flow of a trusted operational evidence construction system provided in an embodiment of the present invention. The diagram illustrates the core components of the system and their collaborative relationships. In the diagram, the business scheduling system acts as the event source, connected to the event monitoring unit. The output of the event monitoring unit simultaneously triggers both fixed-node evidence collection terminals (deployed at the supply end, warehouse, and cabinet) and mobile evidence collection terminals (mounted on vehicles). The collected raw evidence flows into the privacy computing gateway for de-identification processing, and then enters the evidence processing and association unit, where it is bound to a service identifier from the business system. The bound data packet is sent to the trust enhancement unit, which can choose to connect to a blockchain network, a timestamp service, or call a digital signature service. Finally, the processed evidence unit is stored in the evidence storage and retrieval database. The arrows in the diagram clearly indicate the bidirectional or unidirectional flow paths of "operational events" and "evidence data" within the system, reflecting the complete closed loop from event triggering to evidence placement.

[0008] Figure 2This is a flowchart illustrating the steps of a trusted operational evidence construction method according to an embodiment of the present invention. The flowchart strictly defines the execution order of the method. The process begins with "start listening for business operation events." When an event is triggered, the following steps are executed sequentially: "collecting environmental state evidence" -> "performing real-time privacy compliance processing on the evidence" -> "associating and binding the evidence with a business identifier" -> "applying anti-tampering and time-based trustworthiness guarantees to the bound data" -> "storing the guaranteed data as standardized evidence units." Finally, the process returns to the listening state, waiting for the next event. The diamond-shaped decision box in the diagram indicates "whether an event requiring urgent evidence collection (such as a collision) has occurred." If so, the process jumps to the expedited processing branch, demonstrating the method's exception handling capability.

[0009] Figure 3 This is an interactive sequence diagram of event monitoring, triggering, and evidence collection for a single operation of an unmanned vehicle unloading goods at a smart locker in a residential community, as described in one embodiment of the present invention. The diagram visualizes the real-time interaction details within the system. The vertical axis, from top to bottom, represents the lifeline of the "Business Scheduling System," "Event Monitoring Unit," "Vehicle-mounted Evidence Collection Terminal," and "Locker Evidence Collection Terminal." The horizontal timeline depicts the following interaction sequence: 1. The business system generates and publishes a "Unloading Completed" event; 2. The event monitoring unit captures the event; 3. The monitoring unit simultaneously sends a "Start Collection" command to both the vehicle-mounted terminal and the locker terminal; 4. Both ends return "Collection Start" confirmation; 5. After a preset collection period, both ends upload "evidence data"; 6. The monitoring unit confirms receipt and forwards it to the subsequent processing unit. This diagram reveals the high concurrency and collaborative nature of the system's response.

[0010] Figure 4 This is a schematic diagram of the data structure of a standardized service operation evidence unit generated according to an embodiment of the present invention. The diagram breaks down the internal components of the evidence unit in a block diagram format. The core components include: the evidence subject hash value (calculated from the anonymized evidence content), the associated business identifier (such as an order number), the trusted timestamp (from an authoritative time source), the evidence storage credential (such as a blockchain transaction ID or signature value), and the metadata header (containing evidence type, collection device ID, privacy processing identifier, etc.). The logical relationships between the fields are represented by connecting lines, and the overall structure clearly demonstrates the integrity, verifiability, and traceability of the evidence unit.

[0011] Detailed Description of the Embodiments. To enable those skilled in the art to better understand the present invention, a detailed description is provided below in conjunction with the accompanying drawings and embodiments. This embodiment uses "cardiovascular and cerebrovascular emergency drug delivery" as an application scenario in community-based smart elderly care. (Refer to...) Figure 1The trusted operational evidence construction system and the business scheduling system are deployed in parallel. The event monitoring unit subscribes to message topics in the business scheduling system to obtain standardized operational events in real time, such as "Unmanned aerial vehicle successfully picked up goods at the pharmacy" and "Unmanned vehicle completed unloading at the B3 community locker." (Refer to...) Figure 2 and Figure 3 When a specific "unmanned vehicle unloading goods at a smart locker" event occurs: 1. Event Response and Acquisition (S1): The event monitoring unit captures the event and immediately triggers an instruction. The instruction is simultaneously sent to the vehicle-mounted camera on the unmanned vehicle and the cabinet camera deployed in the target smart locker (evidence acquisition unit). Both record the unloading operation process at preset angles, generating original video evidence (environmental state evidence). 2. Privacy Compliance Processing: The original video stream is pushed to the privacy computing gateway (part of the evidence processing unit) in real time. The face / license plate detection model running in the gateway analyzes the video stream frame by frame and dynamically blurs the faces and license plate areas of the identified unrelated personnel. 3. Association Binding (S2): The de-identified video evidence is strongly bound to the delivery waybill number (service business identifier) ​​carried in the business event. This waybill number can be a unique identifier conforming to the ISO / IEC 15459 standard. 4. Trust Enhancement (S3): The bound data packet (containing video hash, waybill number, processing time, etc.) is sent to the trust enhancement unit. This unit calls the API of the blockchain evidence storage client to store the hash value of the data packet on the blockchain and simultaneously obtains proof of the occurrence time of the operation from the National Time Service Center or a commercially trusted third-party timestamp service provider. 5. Evidence Storage on the Blockchain (S4): The evidence storage unit will ultimately form the evidence unit (structure as follows) Figure 4 As shown, the evidence unit (including fields such as evidence content hash, associated waybill number, trusted timestamp, blockchain transaction ID, and privacy processing identifier) ​​is persistently stored. This evidence unit is associated with previous evidence units such as "unmanned aerial vehicle pickup" and "warehouse unloading" generated for this order through the waybill number, forming a complete, tamper-proof, and time-ordered chain of evidence for the drug delivery service operation.

Claims

1. A method for constructing credible operational evidence in automated community emergency services, characterized in that, The process includes an evidence chain construction process executed synchronously with the service process, comprising: S1. Event response and collection: In response to at least one predefined operation event occurring in the service process, automatically collecting environmental state evidence characterizing the occurrence of the event; S2. Association and binding: Associating and binding the collected environmental state evidence with the specific service business identifier that triggered the evidence collection; S3. Trust enhancement: Applying anti-tampering and time reliability guarantees to the evidence data after association and binding; S4. Evidence storage and chain formation: Persistently storing the evidence data after trust enhancement processing to form a service operation evidence unit that can be independently verified afterward.

2. The method according to claim 1, characterized in that, The predefined operation events include at least one of the cargo loading, transportation, unloading, and delivery operations involved in automated logistics services.

3. The method according to claim 2, characterized in that, The automated logistics service includes air transfers performed by unmanned aerial vehicles (UAVs) and ground delivery performed by automated mobile delivery vehicles (AGVs); the predefined operation events specifically include the UAVs' pickup operations at the supply end and unloading operations at the community smart warehouse, as well as the AAVs' loading operations at the community smart warehouse and unloading operations at the community smart service cabinet.

4. The method according to claim 1, characterized in that, The environmental state evidence includes at least one of visual information, auditory information, equipment operation status log information, and spatiotemporal positioning information.

5. The method according to claim 4, characterized in that, Visual information is acquired through the following methods: by visual acquisition devices deployed at fixed nodes and / or by visual acquisition devices mounted on mobile vehicles.

6. The method according to claim 1, characterized in that, The application of anti-tampering and time credibility assurance includes one or a combination of the following methods: (1) submitting evidence data to a network based on a distributed consensus mechanism for storage; (2) using an asymmetric encryption algorithm to digitally sign the evidence data; (3) obtaining a timestamp from the National Time Service Center or a commercially trusted third-party timestamp service provider and binding it with the evidence data.

7. The method according to claim 1, characterized in that, After step S1 and before step S3, there is also a step S2a: privacy compliance processing: automated real-time concealment processing of sensitive personal information of unrelated natural persons that may be contained in the collected original environmental state evidence.

8. The method according to claim 1, characterized in that, The method further includes: when the evidence collection unit or associated sensor detects an abnormal state change in the operating vehicle, automatically triggering and prioritizing the execution of steps S1 to S4, and marking the evidence unit generated this time as high-priority event evidence.

9. A system for constructing credible operational evidence for implementing the method of any one of claims 1-8, characterized in that, include: The event listening unit is used to listen for and capture predefined operation events published in the service process; An evidence collection unit, connected to the event monitoring unit, is used to collect environmental state evidence in response to event triggering; The evidence processing unit is used to associate the evidence data submitted by the evidence collection unit with the corresponding service business identifier and to perform privacy compliance processing. The trust enhancement unit is used to apply tamper-proof and time-reliability guarantees to the data output by the evidence processing unit; The evidence storage unit is used to persistently store the final evidence data after it has been processed by the trust enhancement unit.

10. The system according to claim 9, characterized in that, The trust enhancement unit specifically includes at least one of the following functional modules: a blockchain evidence storage service client, a digital signature calculation module, and a trusted timestamp request client.

Images