Backpack intelligent positioning and anti-theft linkage system based on internet of things

Abstract

This invention discloses an IoT-based intelligent backpack positioning and anti-theft linkage system, belonging to the field of IoT terminal collaboration technology. It includes: a binding module, which initializes and binds a smart backpack, smartphone, and smartwatch to form a unique master collaborator; a monitoring module, in which the smart backpack enters a normal monitoring mode, periodically reports location data, and anonymously hands over with other surrounding devices equipped with the same unit, forming a dynamic device sensing network; a judgment module, which detects and judges abnormal events based on the dynamic device sensing network and sensor data from the smart backpack, generating a theft trigger signal; and a broadcast module, which broadcasts a request for assistance to surrounding devices based on the theft trigger signal. This invention achieves a three-dimensional linkage response, pushing dynamic trajectories to the user's mobile phone, sharing key information with law enforcement platforms, and sending early warnings to devices in high-risk areas, improving the probability of backpack recovery and security response efficiency after theft.

Description

Technical Field

[0001] This invention relates to the field of IoT terminal collaboration technology, and in particular to an IoT-based intelligent backpack positioning and anti-theft linkage system. Background Technology

[0002] With the development of the Internet of Things and positioning technology, smart anti-theft of personal items has become a reality. The current mainstream solution is to integrate GPS, Bluetooth and cellular communication modules into the backpack and pair it with the user's mobile phone. When the backpack and mobile phone are out of Bluetooth connection range or the sensor detects abnormal movement, the backpack will trigger a local alarm and send a location alarm to the mobile phone, realizing basic anti-loss and tracking functions.

[0003] Existing solutions heavily rely on the stolen backpack's own continuous network connectivity and location capabilities. Once the backpack is placed in a signal-blocking bag or moved to a signal dead zone, its active reporting chain is interrupted. The system can only provide the last known static location and cannot continue to track dynamic trajectories, significantly reducing the chances of recovery. Its fundamental limitation lies in the lack of a collaborative and redundant mechanism to maintain tracking even when the target is out of contact. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides an IoT-based intelligent backpack positioning and anti-theft linkage system to solve the problem of tracking interruption after the target device loses its active positioning and communication capabilities.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] This invention provides an IoT-based intelligent backpack positioning and anti-theft linkage system, which includes a binding module for initial binding of a smart backpack, a smartphone, and a smartwatch to form a unique master collaborator;

[0008] The monitoring module allows the smart backpack to enter a normal monitoring mode, periodically report location data, and anonymously handshake with other devices equipped with the same unit in the vicinity to form a dynamic device perception network.

[0009] The judgment module detects and judges abnormal events based on the dynamic device sensing network and sensor data from the smart backpack, and generates a theft trigger signal.

[0010] The broadcast module broadcasts a request for assistance to surrounding devices based on a theft trigger signal, and forms a trusted collaborative network with the devices that respond to the request.

[0011] The reconstruction module generates a digital scent packet of a dynamic verification code derived from the consensus state of the trusted collaborative network, and broadcasts the digital scent packet. Devices in the trusted collaborative network and IoT devices receive and relay the digital scent packet, generating distributed relay records and reconstructing the movement path of the smart backpack after losing the active positioning signal.

[0012] The push module, based on the movement path, initiates a multi-terminal linkage response that pushes the trajectory to smartphones, shares information with law enforcement platforms, and sends warnings to relevant area devices.

[0013] As a preferred embodiment of the IoT-based backpack intelligent positioning and anti-theft linkage system of the present invention, the unique main collaborator includes:

[0014] A physical communication connection is established between the smart backpack, smartphone, and smartwatch;

[0015] In terms of physical communication connections, smart backpacks, smartphones, and smartwatches perform two-way authentication and key exchange.

[0016] Based on the results of two-way authentication and key exchange, the smart backpack, smartphone, and smartwatch form a unique master collaboration entity.

[0017] As a preferred embodiment of the IoT-based backpack intelligent positioning and anti-theft linkage system described in this invention, the reported location data includes:

[0018] The smart backpack activates its positioning and communication functions, enters a low-power normal monitoring mode, and in this mode, the smart backpack collects and reports location data at fixed intervals.

[0019] As a preferred embodiment of the IoT-based backpack intelligent positioning and anti-theft linkage system of the present invention, the dynamic device sensing network includes:

[0020] In normal monitoring mode, the smart backpack broadcasts a beacon signal of a rolling anonymous identifier to the communication range;

[0021] The smart backpack receives broadcasts from other devices in the vicinity equipped with the same unit, and responds to the corresponding scrolling anonymous identifiers with response signals, verifying the format and signature validity of the response signals.

[0022] Other devices equipped with the same unit that respond to the valid verification signal are recorded as neighboring nodes. The information of the devices recorded as neighboring nodes constitutes a dynamic device sensing network.

[0023] As a preferred embodiment of the IoT-based backpack intelligent positioning and anti-theft linkage system of the present invention, wherein: the theft trigger signal includes,

[0024] The smart backpack acquires sensor data and the status of the neighbor node list provided by the dynamic device sensing network. Sensor data analysis determines that the connection of the main collaborator has been abnormally interrupted, which meets the characteristics of involuntary interruption.

[0025] The status analysis of the neighbor node list in the dynamic device sensing network detected that the neighbor nodes simultaneously reported abnormal movement trajectories of the smart backpack.

[0026] The connection interruption judgment result of the main collaborator and the movement trajectory anomaly detection result reported by the neighboring nodes are input into the multi-condition fusion logic decision unit, which outputs a high-risk judgment according to the preset rules.

[0027] A high-risk assessment triggers the generation of a theft trigger signal containing a unique event ID, timestamp, last known location, and trigger reason code.

[0028] As a preferred embodiment of the IoT-based backpack intelligent positioning and anti-theft linkage system of the present invention, the trusted collaborative network includes:

[0029] The smart backpack broadcasts a digital signature assistance request based on a theft trigger signal. The surrounding devices that receive the assistance request verify the validity of the digital signature. Once the verification is successful, the surrounding devices reply with an assistance response to the smart backpack.

[0030] The smart backpack aggregates effective assistance responses and filters the devices that respond to assistance responses based on a pre-stored reputation assessment list;

[0031] Devices with reputation values ​​higher than the threshold after reputation screening are identified as trusted nodes, and a trusted collaborative network is formed based on the identified trusted nodes for this event.

[0032] As a preferred embodiment of the IoT-based backpack intelligent positioning and anti-theft linkage system of the present invention, the broadcast digital scent bag includes:

[0033] The trusted collaborative network of the smart backpack collects temporary identifiers of trusted nodes, sorts and concatenates the temporary identifiers of all trusted nodes to generate an ordered string;

[0034] The smart knapsack performs a hash operation on an ordered string to obtain the consensus state value of the trusted collaborative network;

[0035] The consensus state value of the trusted collaborative network is used to perform a cryptographic hash operation to derive a dynamic verification code;

[0036] The dynamic verification code, the unique event ID, and the hash value of the last known location are encapsulated into a digital scent packet, which is then broadcast at fixed time intervals.

[0037] As a preferred embodiment of the IoT-based backpack intelligent positioning and anti-theft linkage system of the present invention, wherein: the distributed relay record includes,

[0038] Devices and IoT devices in a trusted collaborative network receive broadcast digital odor packets within the communication range, parse the digital odor packets, and extract the dynamic verification code, unique event ID, and hash value of the last known location from the digital odor packets;

[0039] By using dynamic verification codes, combined with locally stored trusted collaborative network status information or pre-set verification logic, the authenticity and timeliness of digital scent packets can be verified.

[0040] After successful verification, the digital scent packet device generates a structured relay record. After generating the relay record, the digital scent packet is rebroadcast at the physical layer as is, enabling the digital scent packet to propagate in the physical space through multi-hop relay between devices, thus expanding the coverage of the tracking signal.

[0041] When the device that receives the digital scent packet connects to the Internet, it encrypts the relay record it generates and uploads it to the designated cloud server via the network connection.

[0042] The cloud server runs continuously, receiving and aggregating encrypted relay records with unique IDs for the same event uploaded from different devices in different geographical locations at different times. After decryption and organization, a distributed relay record set is formed.

[0043] As a preferred embodiment of the IoT-based backpack intelligent positioning and anti-theft linkage system of the present invention, the movement path includes:

[0044] The cloud server performs data cleaning on the distributed relay record set. The cleaned distributed relay record set is then strictly sorted by timestamp to generate time-series relay records.

[0045] Extract the device's current location field from each record in the time-series relay to obtain a series of geographic coordinate points with time stamps, forming a location point sequence;

[0046] The cloud server applies a density-based spatial clustering algorithm to the location point sequence to identify densely populated geographic areas, and uses spline interpolation to connect these densely populated geographic areas, generating a path that describes the continuous spatial changes of the location point sequence.

[0047] The continuously changing path in space is recorded as the inferred movement path of the smart backpack after losing active positioning signal.

[0048] As a preferred embodiment of the IoT-based backpack intelligent positioning and anti-theft linkage system of the present invention, wherein: the multi-terminal linkage response includes,

[0049] The inferred mobile path is encapsulated into a data format and pushed to a smartphone through the data channel of the mobile network.

[0050] Extract event descriptions and backpack identification information associated with theft trigger signals from the event database, package the event descriptions, backpack identification information and inferred movement paths to generate law enforcement notification data packets;

[0051] The system transmits law enforcement notification data packets to the law enforcement platform via a secure API interface. Based on the inferred direction of the movement path, it delineates warning areas in the geofence database and sends anonymous warning messages to all online trusted collaborative network devices and IoT devices located within the warning area.

[0052] The beneficial effects of this invention are as follows: Through the coordinated operation of the binding module, monitoring module, judgment module, broadcasting module, reconstruction module, and push module, a complete security closed loop from theft warning and missing person tracking to multi-terminal linkage is realized. In the monitoring stage, a dynamic device perception network is constructed through anonymous handshake, providing environmental cross-verification for anomaly judgment and improving the accuracy of warnings. In the reconstruction stage, digital scent packets derived from the consensus state of a trusted collaborative network are generated and broadcast, and a wide range of IoT devices are used for opportunistic relay to form distributed relay records. Thus, even after the target backpack loses its active positioning capability, its movement path can still be reconstructed through spatiotemporal analysis of the relay records in the cloud. This solves the pain point of traditional solutions where tracking is interrupted after the target loses contact, and realizes a three-dimensional linkage response that pushes dynamic trajectories to users' mobile phones, shares key information with law enforcement platforms, and sends warnings to devices in risk areas, thereby improving the probability of backpack recovery and security response efficiency after theft. Attached Figure Description

[0053] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a schematic diagram of an IoT-based intelligent backpack positioning and anti-theft linkage system. Detailed Implementation

[0055] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0056] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0057] Secondly, the term "one embodiment" or "example" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the invention. The appearance of an embodiment in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that mutually excludes other embodiments.

[0058] Reference Figure 1 This is one embodiment of the present invention, which provides an Internet of Things-based intelligent backpack positioning and anti-theft linkage system, including the following steps:

[0059] The binding module initializes and binds the smart backpack, smartphone, and smartwatch to form a unique master collaboration entity.

[0060] Establish physical communication connections between smart backpacks, smartphones, and smartwatches.

[0061] Furthermore, the smart backpack's microcontroller initiates the Bluetooth Low Energy protocol stack, putting the smart backpack into a discoverable broadcast mode. The smartphone's operating system calls the Bluetooth application programming interface (API) to enable device scanning. During the scanning cycle, the smartphone's Bluetooth API receives broadcast signals from the smart backpack and smartwatch. The smartphone's operating system parses the device names and identifiers contained in the broadcast signals and lists available smart backpacks and smartwatches on the smartphone's graphical user interface (GUI). The user selects the smart backpack and smartwatch from the list on the smartphone's GUI and triggers a pairing command. Based on the pairing command, the smartphone's operating system initiates connection requests to the smart backpack's microcontroller and the smartwatch's processor. The smart backpack's microcontroller and the smartwatch's processor respond to the connection requests and complete link layer negotiation. After the link layer negotiation is completed, an independent, stable physical layer wireless data channel supporting bidirectional data frame transmission is formed between the smart backpack and the smartphone, and between the smartphone and the smartwatch. A physical communication connection is established between the smart backpack, smartphone, and smartwatch.

[0062] In terms of physical communication connections, smart backpacks, smartphones, and smartwatches perform two-way authentication and key exchange.

[0063] Furthermore, the smartphone generates a cryptographically random number as a challenge and sends it to both the smart backpack and the smartwatch via a physical communication connection. Upon receiving the challenge, the smart backpack and smartwatch each use their pre-installed device private keys to perform a digital signature operation on the challenge. The smart backpack and smartwatch then send the signature results, along with their respective device certificates, back to the smartphone via the physical communication connection. The smartphone uses its pre-installed root certificate public key to verify the validity of the smart backpack and smartwatch's device certificates, and uses the public key from the verified certificates to verify the correctness of the signatures. Upon successful signature verification, the smartphone generates a temporary session key. The smartphone uses the public key from the smart backpack's certificate to encrypt the session key, forming encrypted data packet one, and sends it to the smart backpack via the physical communication connection. The smartphone also uses the public key from the smartwatch's certificate to encrypt the same session key, forming encrypted data packet two, and sends it to the smartwatch via the physical communication connection. The smart backpack and smartwatch each use their respective device private keys to decrypt encrypted data packets one and two, obtaining the same session key. This completes two-way authentication and key exchange between the smart backpack, smartphone, and smartwatch, sharing the same session key.

[0064] Based on the results of two-way authentication and key exchange, the smart backpack, smartphone, and smartwatch form a unique master collaboration entity.

[0065] Furthermore, the smartphone's processor combines the smart backpack's device identifier, the smartwatch's device identifier, and a cryptographically random number generated by the smartphone to create a unique master collaborator identifier. The smartphone's processor then uses a shared session key to encrypt this unique master collaborator identifier, forming encrypted collaborator declaration data. The smartphone's processor transmits this encrypted collaborator declaration data to the smart backpack's microcontroller and the smartwatch's processor via physical communication connections. The smart backpack's microcontroller and the smartwatch's processor use the shared session key to decrypt the encrypted collaborator declaration data, obtaining the unique master collaborator identifier.

[0066] Specifically, the microcontroller of the smart backpack, the processor of the smartphone, and the processor of the smartwatch all store a unique master collaborator identifier and a shared session key in the secure storage area of ​​their respective devices. Based on the stored unique master collaborator identifier and shared session key, the microcontroller of the smart backpack, the processor of the smartphone, and the processor of the smartwatch agree that all subsequent application-layer data communications related to anti-theft monitoring via physical communication connections must use the shared session key for encryption and integrity verification. Each data packet carries a unique master collaborator identifier to declare its communication relationship. Using the unique master collaborator identifier and the shared session key as common credentials, and agreeing on a logical association based on specific communication rules, this relationship is defined as a unique master collaborator. Based on the result of two-way authentication and key exchange, the smart backpack, smartphone, and smartwatch form a unique master collaborator.

[0067] The monitoring module enables the smart backpack to enter a normal monitoring mode, periodically report location data, and anonymously handshake with other devices equipped with the same unit in the vicinity to form a dynamic device perception network.

[0068] The smart backpack activates its positioning and communication functions, entering a low-power normal monitoring mode. In this mode, the smart backpack collects and reports location data at fixed intervals.

[0069] Furthermore, the smart backpack's microcontroller schedules the positioning chip and cellular communication chip, switching them from a shutdown state to a periodic, intermittent operating state. During each awakening period, the positioning chip receives signals from the Global Navigation Satellite System (GNSS) to obtain the smart backpack's latitude and longitude coordinates as location data. The smart backpack's microcontroller then generates a serial number representing the current monitoring period. The location data and serial number are encapsulated into a data packet, which the smart backpack's microcontroller sends to a pre-configured cloud server address via the network connection established by the cellular communication chip. After the location data reporting is complete, the positioning chip and cellular communication chip re-enter a low-power sleep state until the next fixed-interval wake-up time. This cyclical process constitutes the normal monitoring mode that drives the smart backpack to collect and report location data at fixed intervals.

[0070] In normal monitoring mode, the smart backpack broadcasts a beacon signal of a rolling anonymous identifier to the range of communication.

[0071] Furthermore, during the period when the positioning chip is in sleep mode but the Bluetooth Low Energy (BLE) chip remains active, the microcontroller of the smart backpack performs a beacon broadcast task. The microcontroller invokes a cryptographic pseudo-random number generator to generate a new, unassociated rolling anonymous identifier based on the anonymous identifier used in the previous broadcast cycle and a preset seed key. The microcontroller combines the rolling anonymous identifier, a timestamp, and a short code identifying the device type into a string of data. The microcontroller sets this string of data as the payload of the BLE broadcast data packet and instructs the BLE chip to continuously transmit this broadcast data packet at a specific transmit power and broadcast interval. This broadcast data packet serves as the beacon signal for the rolling anonymous identifier. The beacon signal does not contain the smart backpack's actual device address or any personally identifiable information, and the rolling anonymous identifier it carries changes after each broadcast cycle, achieving anonymity and anti-tracking.

[0072] The smart backpack receives broadcasts from other devices in the vicinity that are equipped with the same unit, and responds with corresponding scrolling anonymous identifiers, verifying the format and signature validity of the response signals.

[0073] Furthermore, the Bluetooth Low Energy (BLE) chip in the smart backpack also operates in scanning mode during the intervals between broadcast beacon signals, listening for broadcast data packets on the wireless channel. When the BLE chip captures a broadcast data packet that conforms to a predetermined format, it transmits it as a potential acknowledgment signal to the microcontroller. The smart backpack's microcontroller parses this broadcast data packet and extracts its data payload.

[0074] Specifically, the payload should include a rolling anonymous identifier, a timestamp, a device type code, and a digital signature. The smart backpack's microcontroller first checks whether the format of the rolling anonymous identifier conforms to the protocol specification and whether the timestamp is within a reasonable validity window, completing the initial format verification. Subsequently, the smart backpack's microcontroller uses a pre-stored public key representing a group of devices within the same unit to perform a signature verification operation on the digital signature portion, verifying whether this broadcast data packet was indeed issued by a legitimate device within the same unit. Only when both format verification and signature verification pass are the corresponding response signals for the broadcast data packet considered valid.

[0075] Other devices equipped with the same unit that respond to the valid verification signal are recorded as neighboring nodes. The information of the devices recorded as neighboring nodes constitutes a dynamic device perception network.

[0076] Furthermore, for each valid response signal, the smart backpack's microcontroller extracts the source device's rolling anonymous identifier and timestamp from the response signal. The microcontroller maintains a list of neighbor nodes in the smart backpack's volatile memory. The microcontroller uses the extracted rolling anonymous identifier as an entry key to create or update a record in the neighbor node list.

[0077] Specifically, this record contains at least the following fields: the rolling anonymous identifier of the neighboring device, the timestamp of the most recent valid response signal received, and the wireless signal strength indicator value measured by the Bluetooth Low Energy chip when the response signal was received. The smart backpack's microcontroller also periodically traverses the neighbor node list, deleting records whose most recent communication timestamp differs from the current time by a preset aging threshold to reflect the dynamic departure of neighboring devices. This real-time updated neighbor node list, stored locally on the smart backpack, is essentially a topological snapshot of all interactive, verified co-unit devices within the smart backpack's current physical communication range. This neighbor node list, dynamically constructed and maintained based on response signals, is defined as a dynamic device-aware network.

[0078] The judgment module detects and judges abnormal events based on the dynamic device sensing network and sensor data from the smart backpack, and generates a theft trigger signal.

[0079] The smart backpack acquires sensor data and the status of the neighbor node list provided by the dynamic device sensing network. Sensor data analysis determines that the connection of the main collaborator has been abnormally interrupted, which meets the characteristics of involuntary interruption.

[0080] Furthermore, the microcontroller of the smart backpack reads the current connection status parameters with the smartphone and smartwatch from the Bluetooth Low Energy protocol stack, including the existence of the connection handle, the activity of the link layer connection, and the instantaneous change curve of the received signal strength indicator. The microcontroller reads the raw sampling sequence of the inertial measurement unit's three-axis acceleration and three-axis angular velocity within the most recent time window. The microcontroller analyzes the change curve of the received signal strength indicator to detect whether the signal strength drops sharply from a stable value to an undetectable level in a very short time, rather than exhibiting the typical pattern of smooth decay with increasing distance. The microcontroller analyzes the raw sampling sequence of the inertial measurement unit by comparing whether the magnitude of the acceleration vector and the magnitude of the angular velocity vector show a pulse peak exceeding the normal range of human activity at the same moment of the signal drop. If the sudden drop pattern of the received signal strength indicator highly overlaps in time with the high-impact pulse pattern in the inertial measurement unit data, the sensor data analysis determines that the connection of the main collaborator has experienced an abnormal interruption consistent with the characteristics of involuntary violent pulling or rapid shielding.

[0081] The status analysis of the neighbor node list in the dynamic device sensing network detected that the neighbor nodes simultaneously reported abnormal movement trajectories of the smart backpack.

[0082] Furthermore, the smart backpack's microcontroller retrieves all currently valid neighbor node records from the list of neighbor nodes corresponding to the dynamic device sensing network. The microcontroller analyzes the rolling anonymity identifier and the most recent update timestamp in each neighbor node record. Within a recent, brief analysis window, the microcontroller checks if multiple different neighbor node records have their timestamps marked as updated almost simultaneously, if the rolling anonymity identifier of a neighbor node rapidly becomes expired or is deleted from the list, and if multiple neighbor nodes last sensed the smart backpack's existence at almost the same moment before losing beacon interaction with it. This suggests that the smart backpack may have been rapidly moved out of the shared communication range of these neighbor nodes. The microcontroller interprets this pattern as multiple neighbor nodes simultaneously reporting abnormal movement trajectories of the smart backpack, indicating a rapid, unnatural mass disappearance event of the smart backpack.

[0083] The connection interruption judgment result of the main collaborator and the movement trajectory anomaly detection result reported by the neighboring nodes are input into the multi-condition fusion logic decision unit, which outputs a high-risk judgment according to the preset rules.

[0084] Furthermore, the multi-condition fusion logic decision-maker is a piece of decision logic code running within the smart backpack microcontroller. This decision logic code receives two Boolean input conditions: the first condition is the result of an abnormal interruption of the main cooperative connection determined by sensor data analysis, and the second condition is the result of neighboring nodes simultaneously reporting abnormal movement trajectories detected by dynamic device perception network status analysis. The decision logic code makes judgments based on preset rules. These rules can be set as follows: if both input conditions are true simultaneously, the output is determined to be high risk; or the preset rules can be set as follows: if both the first and second input conditions are true, the output is determined to be extremely high risk; if only the first input condition is true, the output is determined to be medium risk. The smart backpack microcontroller performs logical operations on the two input Boolean conditions according to the currently loaded preset rules and outputs a risk judgment result representing the risk level, such as a high-risk judgment.

[0085] A high-risk assessment triggers the generation of a theft trigger signal containing a unique event ID, timestamp, last known location, and trigger reason code.

[0086] Furthermore, when a high-risk determination is made, the smart backpack's microcontroller immediately executes a signal generation routine. The microcontroller calls a cryptographic random number generator to produce a sufficiently long random number, which is used as the event's unique ID. The microcontroller reads the current Coordinated Universal Time (UTC) from the real-time clock chip as a timestamp. The microcontroller obtains the latitude and longitude coordinates from the most recently successfully reported location data as the last known location. Based on the specific combination of conditions that triggered this high-risk determination, the microcontroller selects the corresponding numerical code from a predefined encoding table as the trigger reason code; for example, code 1 indicates an abnormal interruption of the main cooperative entity and multiple neighboring nodes reporting anomalies. The smart backpack's microcontroller serializes these four data fields—the event's unique ID, timestamp, last known location, and trigger reason code—according to a predetermined data format, combining them into a complete data structure. This data structure, containing all the necessary event summary information, is defined as the theft trigger signal.

[0087] The broadcast module broadcasts assistance requests to surrounding devices based on theft-triggered signals and forms a trusted collaborative network with the devices that respond to the requests.

[0088] The smart backpack broadcasts a digital signature assistance request based on a theft trigger signal. The surrounding devices that receive the assistance request verify the validity of the digital signature. Once the verification is successful, the surrounding devices reply with an assistance response to the smart backpack.

[0089] Furthermore, after generating a theft trigger signal, the smart backpack's microcontroller immediately prepares to broadcast an assistance request. The microcontroller digitally signs the theft trigger signal using the smart backpack's device private key. The microcontroller combines the theft trigger signal with this digital signature and encapsulates it into an assistance request data packet. The smart backpack's microcontroller instructs the Bluetooth Low Energy (BLE) chip to continuously broadcast the assistance request data packet in high-priority mode. Other BLE chips in devices within the broadcast range equipped with the same unit receive this data packet during scanning.

[0090] Specifically, upon receiving the assistance request broadcast signal, the microcontroller of the IoT device equipped with the same functional module capable of verification and response parses the data packet, extracting the theft trigger signal and digital signature. The microcontrollers of other devices verify the digital signature using a pre-installed smart backpack public key. Successful verification results in successful authentication. Upon successful authentication, the microcontroller of the other device that received the assistance request generates an assistance response message containing its own rolling anonymous identifier. The microcontroller of the other device then sends the assistance response message to the smart backpack via a Bluetooth Low Energy chip.

[0091] The smart backpack aggregates effective assistance responses and filters the devices that respond to assistance responses based on a pre-stored reputation assessment list.

[0092] Furthermore, after broadcasting an assistance request, the smart backpack's microcontroller opens a response reception window. During this window, the smart backpack's Bluetooth Low Energy chip receives wireless messages from surrounding devices. The microcontroller filters out received data that conforms to the format of the assistance response message. For each valid assistance response message, the microcontroller extracts the sender's rolling anonymity identifier from the message. The microcontroller then queries a pre-stored reputation assessment list in its local non-volatile memory.

[0093] Specifically, the reputation assessment list stores the reputation scores generated from the historical interaction assessments of different scrolling anonymous identifiers. The smart backpack's microcontroller uses the extracted scrolling anonymous identifier as a query key to look up the corresponding reputation score in the reputation assessment list. If the search is successful, the reputation score is returned; otherwise, a default initial reputation score is assigned to the identifier. The smart backpack's microcontroller records all devices that responded to assistance messages and their retrieved or assigned reputation scores into a list of devices to be filtered for response.

[0094] Devices with reputation values ​​higher than the threshold after reputation screening are identified as trusted nodes, and a trusted collaborative network is formed based on the identified trusted nodes for this event.

[0095] Furthermore, the smart backpack's microcontroller reads a preset reputation screening threshold. The microcontroller iterates through the list of responding devices to be screened, comparing the reputation score of each device with the reputation screening threshold. Devices with a reputation score greater than or equal to the threshold are marked as qualified. The microcontroller extracts the rolling anonymous identifiers of these qualified devices. It adds these rolling anonymous identifiers to a newly created list of trusted node identifiers specifically for this theft event. This list, created and maintained by the smart backpack, contains the rolling anonymous identifiers of all reputation-screened qualified devices in this event; the logical relationships represented by this list constitute the trusted collaborative network for this event.

[0096] The reconstruction module generates a digital scent packet containing a dynamic verification code derived from the consensus state of the trusted collaborative network. This digital scent packet is then broadcast and received and relayed by devices in the trusted collaborative network and IoT devices, generating distributed relay records and reconstructing the smart backpack's movement path after losing its active positioning signal.

[0097] The trusted collaborative network of the smart backpack collects temporary identifiers of trusted nodes, sorts and concatenates the temporary identifiers of all trusted nodes to generate an ordered string.

[0098] Furthermore, the smart backpack's microcontroller accesses the Trusted Collaborative Network data table dynamically created for this event, extracting the core field of all registered entries from the table: the rolling anonymous identifier corresponding to each trusted node. These rolling anonymous identifiers are strings of fixed or variable length. The microcontroller creates a temporary memory buffer to store these extracted rolling anonymous identifier strings. The microcontroller performs a sorting algorithm on these strings in the memory buffer, based on the binary or lexicographical order of the strings.

[0099] Specifically, after sorting, the microcontroller reads each rolling anonymous identifier string from the buffer in sorted order. The microcontroller allocates a new string storage space, copies the first sorted rolling anonymous identifier string into it, and concatenates the second sorted rolling anonymous identifier string to the end of the first string. The microcontroller then concatenates the third, fourth, and so on, up to the last rolling anonymous identifier string to the end of the preceding string in the same way. This final, very long string, containing all trusted node temporary identifiers and with its internal order determined, is the ordered string generated through sorting and concatenation operations.

[0100] The smart knapsack performs a hash operation on an ordered string to obtain the consensus state value of the trusted collaborative network.

[0101] Furthermore, the smart backpack's microcontroller invokes a built-in cryptographically secure hash function calculation engine, such as the SHA-256 algorithm engine. The microcontroller transmits the generated ordered string as input data to the SHA-256 algorithm engine. The SHA-256 algorithm engine performs standard compression function iterations and message expansion on the input ordered string. After completing all rounds of computation, the SHA-256 algorithm engine outputs a fixed-length 256-bit binary sequence. This 256-bit binary sequence is the hash result of the input ordered string. This hash result is defined as the consensus state value of the trusted collaborative network. The consensus state value, in a concise, fixed-length, and irreversible form, uniquely represents the precise membership of the trusted collaborative network at the time the ordered string was generated.

[0102] The consensus state value of the trusted collaborative network is used to perform cryptographic hashing to derive a dynamic verification code.

[0103] Furthermore, the smart backpack's microcontroller prepares to perform a second hash operation to generate a dynamic verification code. The microcontroller reads a long-term, immutable salt value bound to the smart backpack device from a secure storage area. The microcontroller concatenates this salt value with the consensus state value of the trusted collaborative network, forming a new combined data block. The microcontroller again invokes the SHA-256 algorithm engine, taking the combined data block as input. The SHA-256 algorithm engine performs a complete SHA-256 hash calculation on the combined data block, producing another 256-bit output sequence.

[0104] Specifically, the microcontroller extracts a few bits from the beginning of the 256-bit output sequence, for example, the first 64 bits, to form a shorter code. This extracted, shorter code is the dynamic CAPTCHA derived from the consensus state value. The dynamic CAPTCHA inherits the characteristics of a hash function; its value changes with the consensus state value and is difficult to predict.

[0105] The dynamic verification code, the unique event ID, and the hash value of the last known location are encapsulated into a digital scent packet, which is then broadcast at fixed time intervals.

[0106] Furthermore, the microcontroller of the smart backpack retrieves the previously stored theft trigger signal and extracts the unique event ID field from it. The microcontroller then extracts the latitude and longitude coordinates of the last known location from the theft trigger signal. The microcontroller performs a fast hash operation on the latitude and longitude string, for example, using a CRC32 checksum algorithm, to obtain a short hash value as the hash value of the last known location. Following a preset, fixed data packet structure, the microcontroller sequentially arranges the three data fields—dynamic verification code, unique event ID, and hash value of the last known location—into a complete byte array.

[0107] Specifically, the data structure carried by this byte array is the payload of the digital scent packet. The microcontroller of the smart backpack writes this digital scent packet payload byte array into the user-defined data segment of the Bluetooth Low Energy (BLE) broadcast data packet. The microcontroller is configured with a hardware timer, set to a fixed broadcast interval. Whenever the hardware timer generates an interrupt signal, the microcontroller drives the BLE RF front-end to send a BLE broadcast data packet carrying the digital scent packet payload at a specific transmit power and broadcast channel. This broadcast process is continuously and periodically repeated at the fixed time interval set by the hardware timer, realizing the broadcast of the digital scent packet at fixed time intervals.

[0108] Devices and IoT devices in a trusted collaborative network receive broadcast digital odor packets within their communication range, parse the digital odor packets, and extract the dynamic verification code, unique event ID, and hash value of the last known location from the digital odor packets.

[0109] Furthermore, the Bluetooth Low Energy chip in the receiving device captures data packets conforming to a specific broadcast format. The device's microcontroller reads the payload portion of this data packet. The microcontroller parses the payload byte stream according to the known digital scent packet data format definition. The parsing process identifies the start identifier of the data packet and sequentially separates three main data segments from the byte stream according to preset field lengths and orders.

[0110] Specifically, the first data segment is interpreted as a dynamic verification code. The second data segment is interpreted as a unique event ID. The third data segment is interpreted as the hash value of the last known location. The microcontroller completes the parsing and stores these three data fields in a temporary variable, extracting the dynamic verification code, unique event ID, and hash value of the last known location from the digital scent packet.

[0111] By using dynamic verification codes, combined with locally stored trusted collaborative network status information or pre-set verification logic, the authenticity and timeliness of digital scent packets can be verified.

[0112] Furthermore, the microcontroller of the device receiving the digital scent packet reads trusted collaborative network state information associated with the current event from its local non-volatile memory. This state information may include consensus state values ​​or expected dynamic verification code sequences previously received and stored from the smart backpack or other trusted nodes regarding the current event. If the relevant network state information is stored locally, the microcontroller compares the extracted dynamic verification code with the stored expected value to check for a match. If no specific network state information is stored locally, the microcontroller executes pre-defined verification logic, such as performing a reproducible operation on the extracted dynamic verification code and the event's unique ID, comparing the result with a local reference value, or checking whether the format of the dynamic verification code conforms to cryptographic characteristics.

[0113] Specifically, the microcontroller also checks whether the unique event ID is in the locally known list of valid events, or whether the timestamp portion of the unique event ID is within an acceptable time window, to verify timeliness. If the dynamic verification code matches the expected value and the timeliness verification of the unique event ID passes, then the authenticity and timeliness verification of the digital scent package are deemed successful.

[0114] After successful verification, the digital scent packet device generates a structured relay record. After generating the relay record, the digital scent packet is rebroadcast at the physical layer as is, enabling the digital scent packet to propagate in the physical space through multi-hop relay between devices, thus expanding the coverage of the tracking signal.

[0115] Furthermore, upon successful verification, the microcontroller of the device receiving the digital scent packet immediately creates a new data structure to generate a relay record. This relay record data structure contains the following fields: a unique event ID extracted from the digital scent packet, a dynamic verification code extracted from the digital scent packet, a hash value of the last known location extracted from the digital scent packet, the device's local precise timestamp when the digital scent packet was received, the current latitude and longitude coordinates obtained by the device's own GPS positioning chip when the digital scent packet was received, and the signal strength indication value measured by the Bluetooth Low Energy chip when the digital scent packet was received. The microcontroller creates and populates this relay record data structure in the device's memory.

[0116] Specifically, after generating the relay record data structure, the microcontroller immediately performs a rebroadcast operation. The microcontroller completely copies the entire Bluetooth Low Energy broadcast data packet from the received original broadcast data packet, including all physical and link layer fields such as its preamble, access address, and protocol data unit. The microcontroller instructs the device's Bluetooth Low Energy chip to immediately transmit this completely copied original data packet outwards with the same or similar RF parameters as when it was received. This rebroadcast behavior allows the digital scent packet initially emitted by the smart backpack to be rebroadcast by the receiving device, thus having the opportunity to be received by other devices at a greater distance. Through relay-style rebroadcasting between devices, the digital scent packet can transcend the limitations of single-hop communication distance in physical space, propagating through multiple hops and thereby extending the physical coverage of the tracking signal.

[0117] When the device that receives the digital scent packet connects to the Internet, it encrypts the relay record it generates and uploads it to the designated cloud server via the network connection.

[0118] Furthermore, the device that generates the digital scent packet and relay record data structure has a microcontroller that periodically checks the device's network connectivity status. When the device's Wi-Fi or cellular module reports a successful connection to the public internet, the microcontroller triggers the upload process. The microcontroller reads the generated relay record data structure from memory. Using a pre-shared symmetric encryption key, or a public key from a cloud server, the microcontroller performs encryption operations on all bytes of the relay record data structure to generate encrypted data blocks.

[0119] Specifically, the microcontroller encapsulates the encrypted data block, along with a short header identifying the data type, into an application-layer data packet conforming to the transport protocol. The microcontroller then sends this application-layer data packet to the pre-configured IP address and port of the cloud server via an established network connection, such as a TCP socket or an HTTP request. After the upload process is complete, the device can locally delete or archive the uploaded relay records as needed, thus encrypting and uploading its own generated relay records to the designated cloud server.

[0120] The cloud server runs continuously, receiving and aggregating encrypted relay records with unique IDs for the same event uploaded from different devices in different geographical locations at different times. After decryption and organization, a distributed relay record set is formed.

[0121] Furthermore, the cloud server listens on a designated service port on the network, waiting for connections from devices. When a device initiates a connection and uploads an encrypted data packet, the cloud server's network service process receives this packet. The server process parses the packet header, identifying it as an encrypted relay record. Using the decryption key corresponding to the device, the server process decrypts the encrypted data block, recovering the original plaintext relay record data structure. The server process extracts the key index field, the unique event ID, from the relay record. The server process then checks in the cloud server's database or distributed storage, using the unique event ID as the primary key, whether a corresponding record set already exists. If it doesn't exist, a new empty set is created for this unique event ID. The server process adds the decrypted, complete relay record as an entry to the record set corresponding to this unique event ID.

[0122] Specifically, because relay records contain information such as the latitude and longitude coordinates and timestamps of the uploading device, each record added to the collection inherently carries geographical and temporal attributes. The cloud server continuously repeats the process of receiving, decrypting, indexing, and adding records. For the same unique event ID, the cloud server's database will aggregate multiple relay records uploaded from different devices, at different geographical locations, and at different times. This data set, indexed by the unique event ID and containing multiple relay records with spatiotemporal attributes, is the distributed relay record set.

[0123] The cloud server performs data cleaning on the distributed relay record set. The cleaned distributed relay record set is then strictly sorted by timestamp to generate time-series relay records.

[0124] Furthermore, the cloud server's data processing process reads a set of distributed relay records corresponding to a unique event ID from the database. The process iterates through each relay record in the set, validating its fields. Validation includes checking if the timestamp is within a reasonable event time window, if the latitude and longitude coordinates are within the effective range of the Earth's surface, and if the signal strength indication value is within the physically achievable range. The process also identifies and removes anomalous records that are spatially isolated or whose timestamps contradict the majority of other records.

[0125] Specifically, consider records that appear at two geographically distant locations within a very short period. After validity checks and anomaly removal, the remaining records form a cleaned distributed relay record set. The data processing process uses the timestamp field of each record as the sorting key to perform an ascending sort algorithm on this cleaned set. After sorting, the relay records in the set are arranged linearly in chronological order from earliest to latest. The list of relay records arranged in chronological order is the time-series relay record.

[0126] Extract the device's current location field from each record in the time series relay to obtain a series of geographic coordinate points with time stamps, forming a location point sequence.

[0127] Furthermore, the cloud server's data processing process sequentially reads each record in the time-series relay record. For each record read, the data processing process locates the device's current location field within the record structure. This field typically contains two floating-point numbers: longitude and latitude. The data processing process extracts these two floating-point numbers to form a two-dimensional geographic coordinate point, and then extracts the timestamp field from the same record.

[0128] Specifically, the data processing process associates and binds this geographic coordinate point with its corresponding timestamp, creating a geographic coordinate point data pair with a timestamp. The data processing process repeats the above extraction and binding operations for each record in the time series relay record. Finally, the data processing process adds all the extracted and created time-stamped geographic coordinate point data pairs to a new linear data structure in the order they appear in the time series relay record. This new, chronologically ordered linear sequence, where each element contains a geographic coordinate point and its corresponding timestamp, constitutes the location point sequence.

[0129] The cloud server applies a density-based spatial clustering algorithm to the location point sequence to identify densely populated geographical regions, and uses spline interpolation to connect these regions, generating a path that describes the continuous spatial changes of the location point sequence.

[0130] Furthermore, the cloud server's data processing process uses the location point sequence as input to spatial data analysis algorithms. It invokes density-based spatial clustering algorithms, such as the DBSCAN algorithm. The DBSCAN algorithm takes all geographic coordinates in the location point sequence as input, setting a neighborhood radius and a minimum point threshold. The DBSCAN algorithm iterates through all coordinates, marking those with a sufficient number of neighbors within their neighborhood radius as core points, and grouping density-connected core points and boundary points into the same cluster. The output of the DBSCAN algorithm is the division of the coordinates in the location point sequence into one or more clusters, each cluster representing a densely populated geographic area, along with some noise points not assigned to any cluster. The data processing process discards the noise points, retaining the coordinate point clusters corresponding to the identified densely populated geographic areas. The data processing process needs to generate a continuous path for the smart backpack's movement.

[0131] Specifically, for each identified densely populated geographic area, the data processing process obtains the geometric center of all coordinate points within that area, which serves as the representative point for that area. These representative points are then sorted according to the chronological order reflected by the median timestamps of their corresponding coordinate points. The data processing process then applies spline interpolation to this chronologically ordered sequence of representative points. Using the latitude and longitude of these representative points as known data points and the chronological order as parameters, spline interpolation fits a smooth parametric curve that passes through or approximates these representative points. This parametric curve is the path generated by spline interpolation that describes the continuous spatial variation of the location point sequence. This path, given any time parameter, can provide an estimated latitude and longitude position.

[0132] The continuously changing path in space is recorded as the inferred movement path of the smart backpack after losing active positioning signal.

[0133] Furthermore, the cloud server's data processing process converts the path, generated by spline interpolation and describing the continuous spatial variation of a sequence of location points, into a storable and transmittable representation. This representation can be a series of densely sampled points along the path, or it can be the control points and parametric equations of a spline curve. The data processing process associates this path representation with a unique event ID. The data processing process then creates or updates a record in the cloud server's database or path storage service.

[0134] Specifically, this record, indexed by a unique event ID, stores the aforementioned path representation. This trajectory data, stored in the database and associated with a specific theft event, representing the continuous movement of an object over time in two-dimensional geographic space, is physically defined as the inferred movement path of the smart backpack after losing its active positioning signal. This inferred movement path provides an estimate of the smart backpack's possible trajectory during periods when it cannot actively report its location.

[0135] The push module, based on the movement path, initiates a multi-terminal linkage response that pushes the trajectory to smartphones, shares information with law enforcement platforms, and sends warnings to relevant area devices.

[0136] The inferred mobile path is encapsulated into a data format and pushed to the smartphone via the mobile network's data channel.

[0137] Furthermore, the push notification service process on the cloud server reads the inferred movement path of the smart backpack after losing its active positioning signal from the path storage. The push notification service process converts the inferred movement path data, typically a series of timestamped latitude and longitude coordinates, into a common data transmission format, such as JSON or Protocol Buffers. Based on the unique event ID, the push notification service process queries the user-device binding database to find the push token or long-connection session identifier registered by the smartphone of the user associated with the event. The push notification service process combines the encapsulated inferred movement path data with the push target identifier to form a push task.

[0138] Specifically, the push notification service process calls APIs provided by mobile network push service providers, such as Apple's APNs or Google's FCM, or sends push task requests containing inferred mobile path data via a maintained TCP long connection. The mobile network infrastructure works in conjunction with the push service of the smartphone's operating system to deliver the encapsulated inferred mobile path data to the target smartphone's application as a notification or silent message. Upon receiving this data in the background or foreground, the smartphone application parses it and renders and displays the path trajectory on the map component of the user interface.

[0139] Extract event descriptions and backpack identification information associated with theft trigger signals from the event database, package the event descriptions, backpack identification information and inferred movement paths to generate law enforcement notification data packets.

[0140] Furthermore, after completing path deduction, the cloud server's data processing process accesses the event database based on the unique event ID. The event database stores detailed information about the initial theft trigger signal generated by the smart backpack, along with backpack identification information obtained from the binding information, using the unique event ID as the key. The data processing process extracts the trigger cause code, the last known precise location, and the timestamp from the theft trigger signal within the event database; these constitute the core part of the event description. Simultaneously, the data processing process extracts the unique device identifier bound to the smart backpack, such as a serial number or registration code, as the backpack identification information.

[0141] Specifically, the data processing process creates a new data structure for law enforcement notifications. This data structure includes the following fields: event description, backpack identification information, and the inferred movement path of the smart backpack after losing its active positioning signal. The data processing process serializes and encodes this data structure according to the data exchange format pre-agreed upon by the law enforcement platform. The complete byte stream after serialization and encoding constitutes the law enforcement notification data packet. This data packet integrates key law enforcement information such as an event overview, asset identification, and dynamic trajectory.

[0142] The system transmits law enforcement notification data packets to the law enforcement platform via a secure API interface. Based on the inferred direction of the movement path, it delineates warning areas in the geofence database and sends anonymous warning messages to all online trusted collaborative network devices and IoT devices located within the warning area.

[0143] Furthermore, the cloud server's external service process holds API authentication credentials pre-exchanged with the law enforcement platform. The external service process initiates an HTTPS connection to the designated secure API endpoint of the law enforcement platform. In the HTTPS request, the external service process includes the law enforcement notification data packet as the request body payload, along with the necessary API authentication header information. The external service process sends this HTTPS request, thereby transmitting the law enforcement notification data packet to the law enforcement platform through the secure API interface. Simultaneously, the cloud server's geofencing service starts in parallel. The geofencing service analyzes the inferred movement path of the smart backpack after losing its active positioning signal, including the direction of extension and average speed at the end of the path. Based on the direction of extension, speed, and a preset warning lead time, the geofencing service delineates a polygonal or sector-shaped area on the electronic map; this area is the warning zone.

[0144] Specifically, the device communication service on the cloud server queries the device status database to filter out all currently online devices whose last reported location is within the warning area. These devices include those in the trusted collaborative network that participated in this event, as well as other ordinary IoT devices with compatible clients installed. The device communication service generates an anonymous warning message containing an event type code and a simplified map of the warning area, but not user-identified information. The device communication service sends this anonymous warning message to all selected online devices through established push channels or long connections. Devices receiving the warning message can display the warning area on a map or issue local alerts, thus completing area monitoring.

[0145] In summary, this invention achieves a complete security closed loop from theft warning and missing person tracking to multi-terminal linkage through the coordinated operation of binding, monitoring, judgment, broadcasting, reconstruction, and push modules. During the monitoring phase, an anonymous handshake constructs a dynamic device perception network, providing environmental cross-verification for anomaly detection and improving warning accuracy. During the reconstruction phase, digital scent packets encrypted from the consensus state of a trusted collaborative network are generated and broadcast, and a wide range of IoT devices are used for opportunistic relaying to form distributed relay records. This allows the backpack's movement path to be reconstructed through spatiotemporal analysis of the relay records in the cloud even after it loses its active positioning capability. This solves the pain point of traditional solutions where tracking is interrupted after the target loses contact, and achieves a three-dimensional linkage response that pushes dynamic trajectories to users' mobile phones, shares key information with law enforcement platforms, and sends warnings to devices in high-risk areas, improving the probability of backpack recovery and security response efficiency after theft.

[0146] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A backpack intelligent positioning and anti-theft linkage system based on the Internet of Things, characterized in that: include, The binding module initializes and binds the smart backpack, smartphone, and smartwatch to form a unique master collaborator; The monitoring module allows the smart backpack to enter a normal monitoring mode, periodically report location data, and anonymously handshake with other devices equipped with the same unit in the vicinity to form a dynamic device perception network. The judgment module detects and judges abnormal events based on the dynamic device sensing network and sensor data from the smart backpack, and generates a theft trigger signal. The broadcast module broadcasts assistance requests to surrounding devices based on the theft trigger signal and forms a trusted collaborative network with the devices that respond to the requests. The reconstruction module generates a digital scent packet of a dynamic verification code derived from the consensus state of the trusted collaborative network, and broadcasts the digital scent packet. Devices in the trusted collaborative network and IoT devices receive and relay the digital scent packet, generating distributed relay records and reconstructing the movement path of the smart backpack after losing the active positioning signal. The push module, based on the movement path, initiates a multi-terminal linkage response that pushes the trajectory to smartphones, shares information with law enforcement platforms, and sends warnings to relevant area devices.

2. The intelligent positioning and anti-theft linkage system based on the Internet of Things backpack according to claim 1, characterized in that: The unique principal cooperative entity includes, A physical communication connection is established between the smart backpack, smartphone, and smartwatch; In terms of physical communication connections, smart backpacks, smartphones, and smartwatches perform two-way authentication and key exchange. Based on the results of two-way authentication and key exchange, the smart backpack, smartphone, and smartwatch form a unique master collaboration entity.

3. The IoT-based intelligent backpack positioning and anti-theft linkage system as described in claim 2, characterized in that: The reported location data includes, The smart backpack activates its positioning and communication functions, enters a low-power normal monitoring mode, and in this mode, the smart backpack collects and reports location data at fixed intervals.

4. The IoT-based intelligent backpack positioning and anti-theft linkage system as described in claim 3, characterized in that: The dynamic device sensing network includes, In normal monitoring mode, the smart backpack broadcasts a beacon signal of a rolling anonymous identifier to the communication range; The smart backpack receives broadcasts from other devices in the vicinity equipped with the same unit, and responds to the corresponding scrolling anonymous identifiers with response signals, verifying the format and signature validity of the response signals. Other devices equipped with the same unit that respond to the valid verification signal are recorded as neighboring nodes. The information of the devices recorded as neighboring nodes constitutes a dynamic device sensing network.

5. The IoT-based intelligent backpack positioning and anti-theft linkage system as described in claim 4, characterized in that: The theft trigger signal includes, The smart backpack acquires sensor data and the status of the neighbor node list provided by the dynamic device sensing network. Sensor data analysis determines that the connection of the main collaborator has been abnormally interrupted, which meets the characteristics of involuntary interruption. The status analysis of the neighbor node list in the dynamic device sensing network detected that the neighbor nodes simultaneously reported abnormal movement trajectories of the smart backpack. The connection interruption judgment result of the main collaborator and the movement trajectory anomaly detection result reported by the neighboring nodes are input into the multi-condition fusion logic decision unit, which outputs a high-risk judgment according to the preset rules. A high-risk assessment triggers the generation of a theft trigger signal containing a unique event ID, timestamp, last known location, and trigger reason code.

6. The IoT-based intelligent backpack positioning and anti-theft linkage system as described in claim 5, characterized in that: The trusted collaborative network includes, The smart backpack broadcasts a digital signature assistance request based on a theft trigger signal. The surrounding devices that receive the assistance request verify the validity of the digital signature. Once the verification is successful, the surrounding devices reply with an assistance response to the smart backpack. The smart backpack aggregates effective assistance responses and filters the devices that respond to assistance responses based on a pre-stored reputation assessment list; Devices with reputation values ​​higher than the threshold after reputation screening are identified as trusted nodes, and a trusted collaborative network is formed based on the identified trusted nodes for this event.

7. The IoT-based intelligent backpack positioning and anti-theft linkage system as described in claim 6, characterized in that: The broadcast digital scent package includes... The trusted collaborative network of the smart backpack collects temporary identifiers of trusted nodes, sorts and concatenates the temporary identifiers of all trusted nodes to generate an ordered string; The smart knapsack performs a hash operation on an ordered string to obtain the consensus state value of the trusted collaborative network; The consensus state value of the trusted collaborative network is used to perform a cryptographic hash operation to derive a dynamic verification code; The dynamic verification code, the unique event ID, and the hash value of the last known location are encapsulated into a digital scent packet, which is then broadcast at fixed time intervals.

8. The IoT-based intelligent backpack positioning and anti-theft linkage system as described in claim 7, characterized in that: The distributed relay records include, Devices and IoT devices in a trusted collaborative network receive broadcast digital odor packets within the communication range, parse the digital odor packets, and extract the dynamic verification code, unique event ID, and hash value of the last known location from the digital odor packets; By using dynamic verification codes, combined with locally stored trusted collaborative network status information or pre-set verification logic, the authenticity and timeliness of digital scent packets can be verified. After successful verification, the digital scent packet device generates a structured relay record. After generating the relay record, the digital scent packet is rebroadcast at the physical layer as is, enabling the digital scent packet to propagate in the physical space through multi-hop relay between devices, thus expanding the coverage of the tracking signal. When the device that receives the digital scent packet connects to the Internet, it encrypts the relay record it generates and uploads it to the designated cloud server via the network connection. The cloud server runs continuously, receiving and aggregating encrypted relay records with unique IDs for the same event uploaded from different devices in different geographical locations at different times. After decryption and organization, a distributed relay record set is formed.

9. The IoT-based intelligent backpack positioning and anti-theft linkage system as described in claim 8, characterized in that: The movement path includes, The cloud server performs data cleaning on the distributed relay record set. The cleaned distributed relay record set is then strictly sorted by timestamp to generate time-series relay records. Extract the device's current location field from each record in the time-series relay to obtain a series of geographic coordinate points with time stamps, forming a location point sequence; The cloud server applies a density-based spatial clustering algorithm to the location point sequence to identify densely populated geographic areas, and uses spline interpolation to connect these densely populated geographic areas, generating a path that describes the continuous spatial changes of the location point sequence. The continuously changing path in space is recorded as the inferred movement path of the smart backpack after losing active positioning signal.

10. The IoT-based intelligent backpack positioning and anti-theft linkage system as described in claim 9, characterized in that: The multi-terminal linkage response includes, The inferred mobile path is encapsulated into a data format and pushed to a smartphone through the data channel of the mobile network. Extract event descriptions and backpack identification information associated with theft trigger signals from the event database, package the event descriptions, backpack identification information and inferred movement paths to generate law enforcement notification data packets; The system transmits law enforcement notification data packets to the law enforcement platform via a secure API interface. Based on the inferred direction of the movement path, it delineates warning areas in the geofence database and sends anonymous warning messages to all online trusted collaborative network devices and IoT devices located within the warning area.

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