Intelligent insurance claim settlement triggering system based on Internet of Things

Abstract

The invention provides an intelligent insurance claim settlement triggering system based on the Internet of Things technology, and the system collects data in real time through Internet of Things monitoring equipment disposed at the place of an insurance object, and carries out the analysis through a data processing unit. The core of the system is an intelligent claim settlement triggering algorithm which can automatically judge whether claim settlement requirements are met or not according to preset conditions. Once a specific event, such as a vehicle accident, a family fire or a health crisis, is detected, the system automatically triggers a claim settlement process through an intelligent contract to realize quick response. In addition, the system further comprises a user interaction interface, an insurance client and an insurance company are allowed to check the equipment state and the claim settlement progress in real time, and the safety and non-tampering performance of all data are ensured through the block chain technology. According to the system, through real-time monitoring and prediction analysis, the efficiency and customer satisfaction of the insurance industry are improved, the risk and cost are reduced, and an innovative automatic claim settlement solution is provided for the insurance industry.

Description

Technical Field

[0001] The present invention relates to the field of insurance technology, and in particular to an insurance equipment monitoring and claim triggering system combined with Internet of Things technology. Background Art

[0002] In the traditional insurance industry, the monitoring and management of insurance subject matter usually relies on regular manual inspections or proactive reports from customers. This method is not only inefficient, but also difficult to achieve real-time monitoring, resulting in insurance companies often being unable to respond in a timely manner when risks occur. In addition, the claims process usually involves cumbersome paperwork and manual review, which not only prolongs the claims settlement time, but also increases the operating costs of insurance companies.

[0003] With the development of Internet of Things technology, real-time monitoring of the insured object can be achieved by installing sensors and monitoring equipment on the insured object. These devices can collect various data about the insured object, such as temperature, humidity, movement, pressure, etc., and transmit the data to the insurance company. Although this method improves the real-time monitoring, it still relies on human intervention to analyze the data and initiate the claims process when necessary.

[0004] In addition, existing IoT monitoring systems often lack an automated claims triggering mechanism. When an insurance event is detected, the insurance company's claims personnel still need to manually review and process it, which not only increases processing time but also increases the risk of errors. Therefore, it is necessary to develop a system that can automatically respond to monitoring data and trigger the claims process to further improve the efficiency and customer satisfaction of the insurance industry.

[0005] The present invention aims to solve the deficiencies in the prior art and provide an intelligent insurance claims triggering system based on the Internet of Things, which can monitor the status of the insured object in real time and automatically trigger the claims process when a specific event is detected, thereby realizing the automation and intelligence of insurance services. By applying advanced data processing technology, machine learning algorithms, user interaction interfaces, blockchain data storage and smart contracts, this system can improve the risk management capabilities of insurance companies and provide insurance customers with a faster and more convenient claims service experience. Summary of the invention

[0006] The purpose of the present invention is to provide an intelligent insurance claim triggering system based on the Internet of Things, which can monitor the status of the insured object in real time and automatically trigger the claim process when a specific event is detected, so as to improve the efficiency of insurance services and customer satisfaction.

[0007] To achieve the above objectives, the present invention provides the following technical solutions:

[0008] In the insurance claims system, the deployment of IoT monitoring devices is an important step in achieving automated data collection. These devices are customized according to the type of insurance. For example, vehicle insurance may use the on-board diagnostic system (OBD) to track driving habits and vehicle health, while home insurance may deploy smoke and water leak sensors to monitor the safety of the residence. Each device is carefully selected to ensure that it can accurately capture key risk indicators. During the deployment process, each monitoring device needs to be registered on the IoT platform and obtain a set of unique identity credentials, such as product key (ProductKey), device name (DeviceName) and device key (DeviceSecret). This step is key to ensuring data security and device authentication, ensuring the confidentiality and integrity of data during transmission. After registration is completed, the monitoring device will collect data in real time through reliable wireless communication protocols. These protocols may include Wi-Fi, Bluetooth, ZigBee or cellular networks, which can ensure stable data transmission even in harsh environmental conditions. The frequency and type of data collection depends on the function of the monitoring device and the needs of the insurance subject matter. For example, a temperature sensor may record data periodically, while a motion detector may send an alert immediately when abnormal activity is detected. In order to maintain the performance and accuracy of monitoring equipment, regular maintenance and updates are essential. This includes updating the device software, checking and maintaining the hardware, and regularly replacing batteries in battery-powered devices. Through these maintenance work, it can ensure the long-term stable operation of monitoring equipment, providing insurance companies with a continuous flow of risk data, so that they can respond quickly and process claims when insurance events occur.

[0009] The data processing unit is a key component in the insurance claims system, which is responsible for processing the large amount of data collected from IoT monitoring devices. This unit first receives raw data streams from various sensors. This data may include parameters such as temperature, humidity, location, speed, etc., and may be generated at a very high frequency, such as once a second or more frequently. Once the data is received, the data processing unit begins the process of data cleaning. This step is crucial because it ensures the accuracy and reliability of the data. The cleaning process includes removing duplicate data, correcting erroneous values, and handling missing values. For example, if the reading of the temperature sensor is abnormal, such as exceeding 100℃, this value may be identified as an error and deleted or corrected from the data set. Next, the cleaned data needs to be formatted to ensure that all data follows a unified standard. This may involve standardization of timestamps, conversion of units, and unification of data types. Formatted data is easier to compare and analyze. Anomaly detection is another important function of the data processing unit. It uses statistical methods, such as Z-Score or box plot analysis, to identify outliers in the data. These outliers may represent sensor errors, data transmission errors, or other problems and need to be specially handled. When processing a single data source, data fusion technology is also applied to integrate data from multiple monitoring devices. This fusion can be a simple data merging process or it can involve complex algorithms such as Kalman filtering or artificial neural networks to produce a more comprehensive and accurate data analysis result. Finally, the processed data is securely stored in the database and can be encrypted and securely protected to prevent unauthorized access or data tampering. This data provides the basis for subsequent analysis and auditing, and also provides support for claims decision-making. Through these steps, the data processing unit ensures the accuracy, reliability and security of the data, providing a solid data foundation for the insurance claims system.

[0010] The intelligent claim trigger algorithm is the core of the insurance claim system. It analyzes and processes the data transmitted from the IoT monitoring devices by applying machine learning models. The algorithm first pre-processes the data, including normalization and standardization. For example, the temperature data is converted from Celsius to Fahrenheit using the formula Where C is Celsius and F is Fahrenheit. Next, the algorithm enters the feature engineering stage to extract features that have a significant impact on the claims decision, such as the average speed of the vehicle. and emergency braking frequency f brake These features are obtained through the data preprocessing step and used to train the machine learning model. During the model training phase, the algorithm uses the historical claims dataset, which contains detailed information and results of claims cases. By applying supervised learning algorithms, such as support vector machines (SVM), the algorithm learns the relationship between features and claims results. The goal of SVM is to find an optimal hyperplane, which can be expressed as:

[0011]

[0012] Among them, w and b define the hyperplane, φ is the function that maps data to a high-dimensional space, and ξ i is a slack variable, and C is a regularization parameter. In the model evaluation phase, the algorithm uses cross-validation to ensure the generalization ability of the model and calculates performance indicators such as accuracy Acc, recall Recall, and F1 score F1. These indicators are calculated by the following formula:

[0013]

[0014]

[0015] Among them, TP is a true positive, TN is a true negative, FP is a false positive, FN is a false negative, and Precision is the accuracy. When the claim probability P(Claim) predicted by the model exceeds the set value, for example: P(Claim|x)>0.8, the algorithm will trigger the claim process, where x represents the input feature vector. Finally, the algorithm continuously optimizes itself through online learning or incremental learning technology to adapt to new data and trends. The prediction results and feature importance scores are output to the claim decision system to provide a scientific basis for claims, thereby improving the work efficiency and customer satisfaction of insurance companies.

[0016] The user interface plays a vital role in the insurance claims system, providing an intuitive operating platform that allows users to easily manage and track the progress of their insurance claims. The interface design focuses on user experience, ensuring intuitiveness and ease of use, including web interface, mobile application interface or wearable device interface to adapt to the needs and usage scenarios of different users. One of the core functions of the interface is real-time notification, which can push the status update of the insurance subject matter and the change of claim progress to the user. For example, when the OBD device data in the vehicle insurance is detected to be abnormal, the system will automatically send a notification to the user's mobile app to ensure that the user is always updated with the latest information. Historical data query is another important function of the interface, which allows users to query past claims records and the status history of the insurance subject matter at any time. Users can quickly find the information they need by setting filtering conditions such as date range and claim status. The user feedback mechanism is also an indispensable part of the interface. Users can submit their evaluation and suggestions for insurance services through the form. Such feedback is crucial for insurance companies to improve services and enhance user satisfaction. To further enhance the user experience, the interface integrates user behavior analysis tools to analyze user preferences and behavior patterns by tracking user operations on the interface, such as clicks, swipes, and dwell time, and provides personalized services and feedback based on these analysis results. In addition, the interface uses data visualization technology to intuitively display the progress of claims and risk assessment through charts and graphs to help users better understand the insurance status and claims process. At the same time, the interface design takes data security and user security into consideration. The transmission and storage of all user data are encrypted to ensure the security of user information. In order to serve global users, the interface provides multi-language support, and users can choose the interface language according to their language preferences. Moreover, the interface follows the barrier-free design principles to ensure that visually impaired users or other disabled people can also use it conveniently. Through these carefully designed functions and features, the user interaction interface provides users with a comprehensive, intuitive and personalized insurance claims management platform, which significantly improves user participation and satisfaction.

[0017] In the insurance claims system, the role of the blockchain data storage unit is to ensure the security and integrity of the data. First, the data is divided into blocks of equal size before being written to the blockchain. For example, the size of each data block is set to 512KB. Next, each data block is encrypted by the AES-256 encryption algorithm to ensure the security of the data during transmission. After the data is encrypted, a hash value is generated. This is achieved by the SHA-256 hash function, which outputs a 256-bit hash value, providing a unique digital fingerprint for the data block. For high data availability, each data block is replicated into multiple copies, such as 3 copies, and these copies are distributed on storage nodes in different geographical locations. These nodes form a peer-to-peer network. They can be devices of individuals or organizations, and they receive cryptocurrency as rewards by providing storage space. The distributed ledger of the blockchain records the storage transactions of all data blocks, including the location and hash value of the data blocks. Once this information is recorded, it cannot be tampered with. In order to ensure the accuracy and validity of the stored data, the blockchain data storage unit also includes a data verification mechanism. This mechanism regularly audits the hash values ​​of data blocks stored on the blockchain, for example, by comparing the current hash value of the data block with the hash value originally recorded to verify that the data has not been tampered with since it was stored. Finally, in order to protect user information security, the blockchain data storage unit supports authorized access control. This means that only authorized users holding the correct key can access specific data blocks. This authorized access is usually implemented based on asymmetric encryption technology, where the public key is used to encrypt data and the private key is used to decrypt it.

[0018] Smart contracts play a central role in the insurance claims system, and their workflow is highly automated and precise. First, smart contracts are deployed on the blockchain, during which the contract code, parameters, and execution conditions are explicitly written and uploaded to the blockchain network. For example, when a vehicle insurance smart contract is deployed, it will contain vehicle identification information, insurance terms, and specific claim conditions, such as the intensity threshold for collision detection. When an insurance event occurs, such as a vehicle collision, the IoT monitoring device (such as OBD) connected to the smart contract will detect the event and send data. The smart contract confirms whether the event meets the claim conditions through a preset verification process. For example, if the intensity of the vehicle collision exceeds the preset threshold, the smart contract will consider the claim conditions to be met. Once the conditions are verified, the smart contract will automatically execute the claim operation. This includes calculating the amount of compensation and automatically paying the compensation. For example, if the vehicle loss exceeds $1,000, the smart contract will automatically transfer the corresponding amount from the insurance company's account to the car owner's account, without human intervention. The results of all claim operations are recorded on the blockchain, forming an immutable transaction history. These records not only provide an audit trail, but also ensure the transparency and fairness of the claims process, and any authorized user can view these records. Smart contracts also support authorized access control to ensure that only legitimate users can access and view claims-related data. This authorization is usually based on digital signatures and public / private key encryption technology, which ensures the security of data and user information. Finally, smart contracts can include continuous monitoring logic to ensure that the status of the insured object continues to comply with the insurance terms. If any behavior or event that does not comply with the terms is detected, the smart contract can automatically adjust the insurance premium or take other preset measures, such as suspending insurance coverage until the terms are met again.

[0019] The risk assessment module is a key component in the insurance claims system. It evaluates the risk level of the insured object through real-time data analysis and adjusts the insurance premium accordingly. The module first collects data from IoT monitoring devices and user-provided data sources. For example, for vehicle insurance, parameters such as driving speed, driving time, vehicle model, and accident history may be collected. After collecting the data, the module sets risk assessment indicators and thresholds based on the type of insurance. For example, if the vehicle speeds more than three times a month or drives too frequently at night, these may be considered by the system as factors that increase the risk level. Next, statistical models and machine learning algorithms are used to analyze the data to evaluate the risk level of the insured object. For example, the system may use a logistic regression model to predict the probability of a vehicle accident. The formula can be expressed as Where x is the eigenvector, w and b are model parameters. Based on the risk assessment results, the system automatically adjusts the insurance premium. If the assessment results show that the risk level is high, the premium may be increased accordingly; conversely, if the risk level is low, the premium may be reduced or the user may enjoy a premium discount. The system also continuously monitors the status of the insured object and regularly updates the risk assessment to promptly reflect the latest risk status of the insured object. The module generates reports that record the risk indicators and assessment results in detail. These reports can be used for internal audits or to show users the basis for adjusting the insurance premium. If the user disagrees with the risk assessment results, he or she can also provide additional information or file an appeal so that the module can further adjust the assessment results.

[0020] The third-party service integration function in the insurance claims system realizes automated service requests and dispatch by establishing communication protocols with external service providers such as emergency rescue, repair services, and medical assistance. When a claim event occurs, the system will automatically send requests to these service providers based on preset conditions and user needs, and conduct real-time monitoring to ensure the timeliness and quality of the service. In addition, the system can also handle the cost accounting and payment related to third-party services, and continuously optimize the service process through user feedback, thereby providing users with an efficient and convenient claims experience.

[0021] The insurance claims system approach ensures an efficient and transparent claims process through a series of precisely defined steps:

[0022] s1. Deployment of IoT monitoring devices: Install IoT monitoring devices on the insured object, such as installing OBD devices on vehicles to collect driving data, or installing smoke detectors in homes to monitor fire risks. These devices must be tested to ensure that they can operate normally and collect data accurately.

[0023] s2. Receive and analyze data: The data processing unit receives data from the monitoring device in real time. For example, if the vehicle OBD device detects a sudden deceleration, the data processing unit will analyze the data to determine whether a collision has occurred.

[0024] s3. Trigger the claims process: If the analysis results meet the preset claims conditions, such as the acceleration of the vehicle collision exceeds the preset threshold, the intelligent claims trigger algorithm will automatically start the claims process.

[0025] s4. Update users: The user interface will push claims status updates and risk warnings to users in real time. For example, if the vehicle is involved in an accident, the owner will be notified immediately that the claims process has been initiated.

[0026] s5. Use blockchain to store data: All transaction and monitoring data are encrypted and stored on the blockchain. For example, the hash value of vehicle collision data will be recorded on the blockchain to ensure the data is tamper-proof and traceable.

[0027] s6. Execution of smart contracts: Once the claim process is triggered, the smart contract will automatically execute, verify the claim conditions, calculate the amount of compensation, and automatically pay the compensation after confirmation. For example, if the vehicle loss exceeds $1,000, the smart contract will automatically pay the corresponding amount.

[0028] s7. Monitor and evaluate the claims process: The system will continuously monitor the progress of claims and evaluate the effectiveness and efficiency of the claims process based on user feedback and processing results. For example, the system may track the average time from claim initiation to payment.

[0029] s8. Optimize algorithms and processes: Based on monitoring and evaluation results, the system will regularly update the intelligent claims triggering algorithm to improve the accuracy and efficiency of the claims process. For example, the system may adjust the sensitivity of collision detection to reduce false alarms.

[0030] s9. Provide customer support: The system provides customer support functions through the user interaction interface, including customer service requests, question answers, and claims guidance. For example, users can request roadside assistance or medical assistance through the interface.

[0031] s10. Integration of third-party services: The system communicates with third-party service providers and integrates services such as emergency rescue, repair services or medical assistance to provide users with necessary support during the claims process. For example, if a user encounters an accident in a remote area, the system may automatically contact the nearest rescue service.

[0032] The above technical solution can bring the following technical effects:

[0033] 1. Automated claims process to improve efficiency: IoT monitoring devices collect real-time status data of the insured object, such as driving behavior data collected by the vehicle diagnostic system. The intelligent claims trigger algorithm uses this data for real-time analysis. Once an event that meets the claim conditions (such as an accident or failure) is detected, the system will automatically start the claims process. Compared with traditional manual reporting, investigation and damage assessment, the automated process greatly shortens the claims time, achieves minute-level compensation, and improves customer satisfaction.

[0034] 2. Strengthen data security and ensure that information cannot be tampered with: All data collected through IoT devices and transaction information in the claims process are stored on the blockchain, using the distributed ledger technology of the blockchain to ensure the integrity and immutability of the data. The data is encrypted before being uploaded to the blockchain to ensure the security of the transmission process and prevent the data from being intercepted or tampered with during the transmission process. The decentralized nature of the blockchain eliminates the risk of single point failures, enhances the data's ability to resist attacks, and ensures the continuity and reliability of the insurance business.

[0035] 3. Optimize customer interaction and improve service experience: The user interaction interface provides an intuitive operation interface, allowing customers to easily view the real-time status of the insurance subject matter and the progress of claims, improving service transparency. The interface provides real-time notification functions to ensure that customers can receive updates at each key node in the claims process, reducing customers' waiting anxiety. Through the integrated feedback mechanism, customers can directly make service requests or complaints through the system, and insurance companies can respond quickly and provide solutions, enhancing customer participation and satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic diagram of the insurance claim system of the present invention

[0037] Figure 2 This is the step diagram of the claim settlement process of the present invention DETAILED DESCRIPTION

[0038] The following will be combined with the attached embodiment of the present invention Figure 1 and Figure 2 , the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] In the insurance claims system, the deployment of IoT monitoring devices is the key to ensuring data accuracy and real-time performance. First, for different insurance scenarios, such as vehicle insurance or home insurance, select appropriate monitoring devices for deployment. For example, installing an on-board diagnostic system (OBD) in a vehicle can monitor the vehicle's operating status in real time, including parameters such as speed, acceleration, and braking status. These data are essential for assessing the severity of vehicle accidents. During the deployment process, each monitoring device needs to be registered in the IoT platform and obtain a unique set of identity credentials, including product key (ProductKey), device name (DeviceName), and device key (DeviceSecret). This step ensures the legitimacy of the device and the security of data transmission. After registration, the device collects data in real time and sends it to the data processing unit through wireless communication protocols such as Wi-Fi, Bluetooth, ZigBee, or cellular networks. The frequency and type of data collection depends on the function of the monitoring device and the requirements of the insurance subject matter. For example, a temperature sensor may collect data every 5 seconds, while a smoke detector will immediately send an alarm signal when it detects that the smoke concentration exceeds the preset threshold of 50 micrograms per cubic meter. These data are essential for quickly responding to insurance events and accurately assessing claims needs. In order to maintain the performance and accuracy of monitoring equipment, regular maintenance and updates are essential. This includes software updates, hardware overhauls, and regular battery replacement in battery-powered devices. Through these maintenance work, it can ensure the long-term stable operation of monitoring equipment, providing insurance companies with a continuous flow of risk data, so that they can respond quickly and process claims when insurance events occur.

[0040] In the insurance claims system, the data processing unit plays a vital role in converting the raw data collected by IoT monitoring devices into useful information. These monitoring devices may collect data once a second, generating a data stream containing parameters such as temperature, humidity, location, speed, etc. For example, a vehicle's OBD device may record speed data, and the normal driving speed range is 40-120 km / h, and any readings outside this range may be marked as abnormal. The data processing unit first cleans the data to remove abnormal values ​​that may be caused by sensor errors or data transmission problems. For example, if a temperature sensor suddenly records a reading of 500℃, this obviously unreasonable value will be identified and excluded from the data set. The cleaning process may include the use of statistical methods, such as calculating the Z-Score, and any value exceeding 3 times the standard deviation is considered an anomaly. Next, the data is formatted and standardized to ensure consistency. This may involve converting all temperature data from Celsius to Fahrenheit, or ensuring that all timestamps follow the same 24-hour format. For example, if the timestamps in the data set are not in the same format, such as some are "hours: minutes: seconds" and others are "hours / minutes / seconds", the data processing unit will unify them into a standard format. Anomaly detection is an ongoing process that uses box plot analysis to identify outliers that may represent errors or system failures. For example, if a data point falls outside the box plot, that is, more than 1.5 times the interquartile range, it will be marked as a potential outlier for further investigation. Finally, data from multiple monitoring devices are fused together to provide a comprehensive data analysis result. This may involve combining vehicle location data with speed data to calculate the vehicle's travel path. For example, if the vehicle's location data shows that it moved from one city to another in a short period of time, and the speed data shows an average speed of 60 kilometers per hour, then the data will be fused to assess the rationality of the trip. The processed data will be securely stored in the database and encrypted to protect the data from unauthorized access or tampering. The data provides the basis for subsequent analysis and auditing, and also provides support for claims decisions. Through these steps, the data processing unit ensures the accuracy, reliability and security of the data, providing a solid data foundation for the insurance claims system.

[0041] The intelligent claim trigger algorithm is the core of the insurance claim system. It analyzes and processes the data transmitted from the IoT monitoring devices by applying machine learning models. The algorithm first pre-processes the data, including normalization and standardization. For example, the temperature data is converted from Celsius to Fahrenheit using the formula Where C is Celsius and F is Fahrenheit. Next, the algorithm enters the feature engineering stage to extract features that have a significant impact on the claims decision, such as the average speed of the vehicle. and emergency braking frequency f brake。 These features are obtained through the data preprocessing step and used to train the machine learning model. During the model training phase, the algorithm uses the historical claims data set, which includes the details and results of the claims cases. By applying supervised learning algorithms, such as support vector machines (SVM), the algorithm learns the relationship between features and claims results. The goal of SVM is to find an optimal hyperplane, which can be expressed as:

[0042]

[0043] y i (w·φ(x i )+b)≥1-ξ i ,ξ i ≥0

[0044] Among them, w and b define the hyperplane, φ is the function that maps data to a high-dimensional space, and ξ i is the slack variable and C is the regularization parameter.

[0045] In the model evaluation phase, the algorithm uses cross-validation to ensure the generalization ability of the model and calculates performance indicators such as accuracy Acc, recall Recall and F1 score F1. These indicators are calculated by the following formula:

[0046]

[0047] Among them, TP is a true positive, TN is a true negative, FP is a false positive, FN is a false negative, and Precision is the accuracy. When the claim probability P(Claim) predicted by the model exceeds the set value, for example: P(Claim|x)>0.8, the algorithm will trigger the claim process, where x represents the input feature vector. Finally, the algorithm continuously optimizes itself through online learning or incremental learning technology to adapt to new data and trends. The prediction results and feature importance scores are output to the claim decision system to provide a scientific basis for claims, thereby improving the work efficiency and customer satisfaction of insurance companies.

[0048] The user interface plays a vital role in the insurance claims system, providing an intuitive and easy-to-use management platform. The interface can send notifications to users' mobile phones or email addresses within 30 seconds of an insurance event through real-time notifications. For example, when the vehicle's OBD device detects a collision and activates, the user will receive a notification immediately. In terms of historical data query, the interface allows users to customize query parameters, such as selecting claims records in the last 6 months, and filter by claim status (such as pending review, processing, and completed). The query results will be displayed within 2 seconds after the user initiates the request, ensuring that users can quickly obtain the required information. The user feedback mechanism is equally important. Users can rate the service from 1 to 5 stars and attach a text comment of up to 500 words. After the feedback is submitted, the insurance company's customer service team will respond to the user's feedback within 1 working day to improve the service quality. The user behavior analysis tool in the interface tracks the user's behavior on the interface. For example, if the average stay time of the user on the claim progress page exceeds 3 minutes, the system will automatically prompt the user if he needs help in order to provide more personalized services. The data visualization function displays the progress of claims through graphics, such as using a progress bar to display the progress of claims. The loading time of the progress bar does not exceed 1 second, ensuring that users can intuitively see the current stage of claims processing. In terms of security, all user data is transmitted using at least 128-bit SSL encryption technology to ensure the security of data during transmission. The stored data is also encrypted, and the access rights of user information are controlled at level 5 or above to prevent unauthorized access. Multi-language support covers more than 10 languages ​​including Chinese, English, and Spanish. Users can choose the interface language according to their language preferences to ensure that users around the world can use the system without obstacles. In terms of barrier-free design, the interface provides functions such as text magnification, high contrast mode, and screen reader compatibility, so that visually impaired users or other disabled people can also use it conveniently. Through these specific functions and parameter settings, the user interaction interface provides users with a comprehensive, intuitive and personalized insurance claims management platform, which significantly improves user participation and satisfaction.

[0049] The blockchain data storage unit plays a key role in the insurance claims system, which uses blockchain technology to ensure the security, integrity and immutability of data. The process first involves splitting the claims-related data into small blocks, for example, each data block is set to 512KB in size, and then encrypting these data blocks with AES-256 to ensure the security of the data during transmission. Next, each encrypted data block will generate a unique hash value through a hash function such as SHA-256, which is the digital fingerprint of the data block for subsequent data integrity verification. For high data availability, each data block will be replicated multiple times, such as 3 copies, and these copies will be distributed on storage nodes in different geographical locations. These storage nodes may be operated by different organizations or individuals, who receive cryptocurrency as rewards by providing storage space. All data storage transactions, including the location, hash value and replication information of the data block, will be recorded in the blockchain ledger, ensuring the transparency and verifiability of the data. In order to ensure the accuracy and validity of the stored data, the blockchain data storage unit also contains a data verification mechanism, which will regularly audit the hash value of the data block stored on the blockchain. In addition, in order to protect information security and data security, blockchain data storage units support authorized access control, and only authorized entities can access specific data blocks, which is usually achieved based on public and private key encryption technology.

[0050] The use of smart contracts in insurance claims systems represents the future of automation and transparency in the insurance industry. First, smart contracts are deployed on the blockchain and contain parameterized settings for claim conditions. For example, a car insurance contract may set that if the vehicle is hit and the damage exceeds $1,000, the smart contract will automatically trigger the claim process. When an insurance event occurs, such as a vehicle collision, the IoT monitoring device connected to the smart contract detects the event and sends data. The smart contract confirms whether the event meets the claim conditions through a preset verification process. For example, if the intensity of the vehicle collision exceeds a set threshold, the smart contract will consider the claim conditions to be met. Once the conditions are verified, the smart contract will automatically execute the claim operation. This includes calculating the claim amount using a predetermined formula, such as the claim amount = the assessed damage amount x (1-deductible rate). This calculation ensures the accuracy and fairness of the claim amount. After confirming the claim conditions, the smart contract will automatically transfer the claim amount from the insurance company's account to the car owner's account. This process does not require human intervention and is usually completed within a few minutes, greatly improving the efficiency of claims. The results of all claims operations are recorded on the blockchain, forming an immutable transaction history. These records can not only be used for auditing and verification, but also ensure the transparency and fairness of the claims process. Finally, smart contracts support authorized access control, ensuring that only authorized users (such as insurance claims personnel) can access and view claims-related data. This authorization is usually based on digital signatures and public / private key encryption technology, which ensures data security and user information security. Through these steps, smart contracts provide an automated, transparent and efficient solution for the insurance claims system, reducing the possibility of human error and fraud, while improving the speed and accuracy of claims.

[0051] The risk assessment module is a key component in the insurance claims system. It evaluates the risk level of the insured object through real-time data analysis and adjusts the insurance premium accordingly. The module first collects data from IoT monitoring devices and user-provided data sources. For example, for vehicle insurance, parameters such as driving speed, driving time, vehicle model, and accident history may be collected. After collecting the data, the module sets risk assessment indicators and thresholds based on the type of insurance. For example, if the vehicle speeds more than three times a month or drives too frequently at night, these may be considered by the system as factors that increase the risk level. Next, statistical models and machine learning algorithms are used to analyze the data to evaluate the risk level of the insured object. For example, the system may use a logistic regression model to predict the probability of a vehicle accident. The formula can be expressed as Where x is the eigenvector, w and b are model parameters. Based on the risk assessment results, the system automatically adjusts the insurance premium. If the assessment results show that the risk level is high, the premium may be increased accordingly; conversely, if the risk level is low, the premium may be reduced or the user may enjoy a premium discount. The system also continuously monitors the status of the insured object and regularly updates the risk assessment to promptly reflect the latest risk status of the insured object. The module generates reports that record the risk indicators and assessment results in detail. These reports can be used for internal audits or to show users the basis for adjusting the insurance premium. If the user disagrees with the risk assessment results, he or she can also provide additional information or file an appeal so that the module can further adjust the assessment results.

[0052] The third-party service integration function in the insurance claims system realizes automated service requests and dispatch by establishing communication protocols with external service providers such as emergency rescue, repair services and medical assistance. When a claim event occurs, such as a vehicle collision, the system will automatically send requests to these service providers based on preset conditions and user needs, and ensure that the initial response of emergency rescue operations is completed within 30 minutes. At the same time, the system will continuously monitor the execution of the service and provide on-site support within 5×8 hours after the service is completed to ensure the quality of service. In addition, the system is also able to handle the cost accounting and payment related to third-party services, which is usually completed within 24 hours after the service is completed. User feedback will also be collected and analyzed to continuously optimize the service process, thereby providing users with an efficient and convenient claims experience.

[0053] The insurance claims system approach ensures an efficient and transparent claims process through a series of precisely defined steps:

[0054] s1. Deployment of IoT monitoring devices: Install IoT monitoring devices on the insured object, such as installing OBD devices on vehicles to collect driving data, or installing smoke detectors in homes to monitor fire risks. These devices must be tested to ensure that they can operate normally and collect data accurately.

[0055] s2. Receive and analyze data: The data processing unit receives data from the monitoring device in real time. For example, if the vehicle OBD device detects a sudden deceleration, the data processing unit will analyze the data to determine whether a collision has occurred.

[0056] s3. Trigger the claims process: If the analysis results meet the preset claims conditions, such as the acceleration of the vehicle collision exceeds the preset threshold, the intelligent claims trigger algorithm will automatically start the claims process.

[0057] s4. Update users: The user interface will push claims status updates and risk warnings to users in real time. For example, if the vehicle is involved in an accident, the owner will be notified immediately that the claims process has been initiated.

[0058] s5. Use blockchain to store data: All transaction and monitoring data are encrypted and stored on the blockchain. For example, the hash value of vehicle collision data will be recorded on the blockchain to ensure the data is tamper-proof and traceable.

[0059] s6. Execution of smart contracts: Once the claim process is triggered, the smart contract will automatically execute, verify the claim conditions, calculate the amount of compensation, and automatically pay the compensation after confirmation. For example, if the vehicle loss exceeds $1,000, the smart contract will automatically pay the corresponding amount.

[0060] s7. Monitor and evaluate the claims process: The system will continuously monitor the progress of claims and evaluate the effectiveness and efficiency of the claims process based on user feedback and processing results. For example, the system may track the average time from claim initiation to payment.

[0061] s8. Optimize algorithms and processes: Based on monitoring and evaluation results, the system will regularly update the intelligent claims triggering algorithm to improve the accuracy and efficiency of the claims process. For example, the system may adjust the sensitivity of collision detection to reduce false alarms.

[0062] s9. Provide customer support: The system provides customer support functions through the user interaction interface, including customer service requests, question answers, and claims guidance. For example, users can request roadside assistance or medical assistance through the interface.

[0063] s10. Integration of third-party services: The system communicates with third-party service providers and integrates services such as emergency rescue, repair services or medical assistance to provide users with necessary support during the claims process. For example, if a user encounters an accident in a remote area, the system may automatically contact the nearest rescue service.

[0064] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An intelligent insurance claim triggering system based on the Internet of Things, the system comprising: An IoT monitoring device, deployed on the subject matter of insurance, for collecting status data in real time, the IoT monitoring device includes but is not limited to a temperature sensor, a humidity sensor, a motion detector, a pressure sensor, a smoke detector, a gas leak detector, a health monitoring device or a vehicle diagnostic system, the device communicates with the data processing unit via a wireless communication protocol; A data processing unit, used to receive data from the IoT monitoring device and perform preliminary analysis, including data cleaning, formatting and anomaly detection, to ensure the accuracy and reliability of the data; an intelligent claims triggering algorithm, used to analyze the data provided by the data processing unit and trigger the claims process when the preset conditions are met, the algorithm includes a machine learning model that can learn historical data and user behavior to improve the accuracy of the prediction; a user interaction interface, allowing the user to view the status of the insured object and the progress of the claims in real time, the user interaction interface includes but is not limited to a web interface, a mobile application interface or a wearable device interface, providing real-time notification, historical data query and user feedback functions; a blockchain data storage unit, used to store all transaction and monitoring data to ensure the security, integrity and immutability of the data, the blockchain data storage unit supports encryption and authorized access to the data; a smart contract, connected to the intelligent claims triggering algorithm, used to automatically execute the claims operation when the claims process is triggered, the smart contract includes an automatic payment mechanism, used to automatically pay the compensation when the claims conditions are met.

2. The system of claim 1, wherein the IoT monitoring device further comprises a self-diagnosis module for monitoring the health of the device itself and automatically reporting when an abnormality is detected.

3. The system according to claim 1, wherein the data processing unit further comprises a data fusion module for integrating data from multiple monitoring devices and providing a comprehensive data analysis result.

4. The system of claim 1, wherein the intelligent claims triggering algorithm is capable of receiving information from external data sources and incorporating it into the claims decision-making process.

5. The system according to claim 1, wherein the user interaction interface also includes a user behavior analysis tool for analyzing the user's interaction with the interface and providing personalized services and feedback.

6. The system according to claim 1, wherein the blockchain data storage unit further comprises a data verification mechanism for ensuring the accuracy and validity of the stored data.

7. The system of claim 1, wherein the smart contract can be customized according to different insurance products and terms.

8. The system according to claim 1 further comprises a risk assessment module for assessing the risk level of the subject matter of insurance in real time and adjusting the insurance premium rate according to the assessment result.

9. The system of claim 1, wherein the system is capable of communicating with a third-party service provider to provide necessary services in the claims process, such as emergency rescue, repair services, or medical assistance.

10. A method of using the system according to any one of claims 1 to 9, comprising the following steps: s1. Deploy IoT monitoring equipment and collect data, including installing the monitoring equipment on the subject matter of insurance and ensuring the normal operation of the equipment and accurate data collection; s2. Receive and analyze data, and process and analyze the collected data in real time through the data processing unit to identify any anomalies or potential risks; s3. The claims process is triggered based on the analysis results. The intelligent claims trigger algorithm evaluates the processed data. If the data meets the preset claims conditions, the claims process is automatically initiated. s4. Update users through the user interface, where the system sends real-time notifications to users, including claim status updates, risk warnings, and other relevant information; s5. Use blockchain to store data. All transaction and monitoring data are encrypted and stored on the blockchain to ensure the data is tamper-proof and traceable; s6. Execute smart contracts to complete claims. Once the claims process is triggered, the smart contract will automatically execute, including verifying the claims conditions, calculating the claims amount, and automatically paying the claims; s7. Monitor and evaluate the claims process. The system continuously monitors the claims progress and evaluates the effectiveness and efficiency of the claims process based on feedback and results; s8. Optimize algorithms and processes. Based on monitoring and evaluation results, the system regularly updates the intelligent claims triggering algorithm to improve the accuracy and efficiency of the claims process; s9. Provide customer support. The system provides customer support functions through the user interface, including customer service requests, question answers and claims guidance; s10. Integration of third-party services. The system communicates with third-party service providers to provide necessary services in the claims process, such as emergency rescue, repair services or medical assistance.

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