Intelligent old-age care life assisting and monitoring early warning system

Abstract

The invention discloses an intelligent old-age care life assisting and monitoring early-warning system, and the system comprises a sensing layer which comprises a health sensing node, a safety sensing node, and an interaction and assisting node; the signal receiving end of the monitoring and early warning mechanism is arranged at the signal output end of the intelligent processing layer, and the monitoring and early warning mechanism comprises graded early warning response and privacy protection enhancement. According to the intelligent life assisting and monitoring early warning system for the aged, the sensing layer comprising the health sensing node, the safety sensing node and the interaction and assisting node is arranged, so that life data of the aged can be monitored in real time; and by setting an intelligent processing layer comprising a health risk dynamic assessment engine, resource scheduling intelligent optimization and multi-modal data fusion enhancement, only necessary results can be uploaded to the cloud, and a data processing link is greatly shortened.

Description

Technical Field

[0001] This invention relates to the field of early warning system technology, specifically to an intelligent elderly care living assistance and monitoring early warning system. Background Technology

[0002] The "Architectural Design Standard for Elderly Care Facilities" (JGJ 450-2018) specifies the functions of community-based elderly care facilities (CSCFS), including living spaces, recreational and fitness spaces, and rehabilitation and medical spaces. Paying attention to the design of living spaces for the elderly can improve their quality of life and better address the challenges of an aging population.

[0003] In existing technologies, most systems rely on cameras for continuous monitoring, which infringes on the privacy of the elderly; the data processing of most systems depends on the cloud, resulting in high latency and high privacy risks. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of the embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0005] 1. Technical problems to be solved:

[0006] To address the issues mentioned above, most systems rely on continuous camera monitoring, which infringes on the privacy of the elderly; and most systems rely on cloud processing, resulting in high latency and high privacy risks.

[0007] Therefore, the purpose of this invention is to provide an intelligent elderly care living assistance and monitoring early warning system, which collects only the data necessary for risk warning and can process information quickly.

[0008] 2. Technical Solution:

[0009] To address the aforementioned technical problems, according to one aspect of the present invention, the present invention provides the following technical solution:

[0010] A smart elderly care living assistance and monitoring early warning system includes: a perception layer, which includes health perception nodes, safety perception nodes and interaction and assistance nodes;

[0011] The transmission layer has a signal receiving end located at the signal output end of the sensing layer.

[0012] The intelligent processing layer has its signal receiving end located at the signal output end of the transmission layer. The intelligent processing layer includes a dynamic health risk assessment engine, intelligent resource scheduling optimization, and multimodal data fusion enhancement.

[0013] The application service layer has a signal receiving end located at the signal output end of the intelligent processing layer. The application service layer includes an elderly end, a family member end, a caregiver end, and a management end.

[0014] A monitoring and early warning mechanism is provided, wherein the signal receiving end of the monitoring and early warning mechanism is set at the signal output end of the intelligent processing layer, and the monitoring and early warning mechanism includes graded early warning response and enhanced privacy protection.

[0015] As a preferred embodiment of the intelligent elderly care living assistance and monitoring early warning system of the present invention, the health sensing node includes: an environmental millimeter-wave radar, a bioelectric sensor, and a bathroom millimeter-wave radar. The environmental millimeter-wave radar monitors respiratory rate and heart rate. The bioelectric sensor is installed on the user and collects blood pressure and blood oxygen. The bathroom millimeter-wave radar monitors bathing time.

[0016] As a preferred embodiment of the intelligent elderly care living assistance and monitoring early warning system of the present invention, the safety sensing node includes: a gas sensor, a water immersion sensor and a binocular camera. The signal output terminals of the gas sensor and the water immersion sensor are provided with signal receiving terminals of valves. The binocular camera is installed on the user and is set to be activated by event triggering.

[0017] As a preferred embodiment of the intelligent elderly care living assistance and monitoring early warning system of the present invention, the interaction and assistance nodes include: a service interaction terminal and an age-friendly device. The service interaction terminal is equipped with a voice terminal and a touch terminal. The voice terminal is located inside the service interaction terminal, and the touch terminal can back up the collected data.

[0018] As a preferred embodiment of the intelligent elderly care living assistance and monitoring early warning system of the present invention, the age-friendly equipment includes: an intelligent walking aid, a nursing bed, and a bathing aid. The intelligent walking aid is installed on the user and can avoid obstacles and cushion falls. The nursing bed can assist with sleep, and the bathing aid can assist with bathing.

[0019] As a preferred embodiment of the intelligent elderly care living assistance and monitoring early warning system of the present invention, the transmission layer includes an edge computing server, a LoRa IoT gateway, and an emergency backup power supply. The edge computing server can process sensitive health data locally, the LoRa IoT gateway can connect to sensors within a radius of 500 meters, and the emergency backup power supply can support continuous operation for 4 hours after a power outage. The transmission methods of the transmission layer include 5G, LoRa, and Bluetooth Mesh transmission. LoRa transmission can transmit low-frequency data, 5G transmission can transmit high-frequency health data, and Bluetooth Mesh transmission can link with local devices.

[0020] As a preferred embodiment of the intelligent elderly care living assistance and monitoring early warning system of the present invention, the health risk dynamic assessment engine is configured to be based on LSTM neural network, and the health risk dynamic assessment engine can perform "behavior-physiology" correlation analysis. The resource scheduling intelligent optimization improved ant colony algorithm is a three-dimensional model of "demand priority-distance-load". The resource scheduling intelligent optimization supports real-time dynamic allocation of community service resources. The multimodal data fusion enhancement introduces a federated learning framework. The multimodal data fusion enhancement can protect data privacy and fuse sensor data across devices.

[0021] As a preferred embodiment of the intelligent elderly care living assistance and monitoring early warning system of the present invention, the elderly terminal can be fully voice-interactive, the family member terminal APP has added a "risk trend chart", the caregiver terminal supports remote setting of "safety fences", the management terminal can integrate the service work order system and the government supervision platform, and the management terminal has a "service quality traceability" function.

[0022] As a preferred embodiment of the intelligent elderly care living assistance and monitoring early warning system of the present invention, the graded early warning response includes a first-level early warning, a second-level early warning, and a third-level early warning. The first-level early warning includes minor abnormalities, and after the first-level early warning is triggered, a terminal voice reminder and a silent push notification to the family's APP are issued. The second-level early warning includes potential risks, and after the second-level early warning is triggered, a community grid worker is automatically dispatched to visit the home. The third-level early warning includes emergency events, and after the third-level early warning is triggered, a local sound and light alarm is triggered, a family location notification is issued, and a dispatch is issued by the community emergency team.

[0023] As a preferred embodiment of the intelligent elderly care living assistance and monitoring early warning system of the present invention, the enhanced privacy protection includes local storage of sensitive data on an edge server, transmission of only encrypted risk assessment results in the cloud, and local caching of camera videos for only 24 hours.

[0024] 3. Beneficial effects:

[0025] Compared with the prior art, the beneficial effects of the present invention are:

[0026] This intelligent elderly care living assistance and monitoring early warning system, by setting up a perception layer including health perception nodes, safety perception nodes, and interaction and assistance nodes, can monitor the elderly's living data in real time without infringing on their privacy.

[0027] This intelligent elderly care living assistance and monitoring early warning system, by setting up an intelligent processing layer that includes a dynamic health risk assessment engine, intelligent resource scheduling optimization, and multimodal data fusion enhancement, can upload only the necessary results to the cloud, significantly shortening the data processing link. Attached Figure Description

[0028] To more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and detailed embodiments. 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. Wherein:

[0029] Figure 1 This is a schematic diagram of the overall structure of an intelligent elderly care living assistance and monitoring early warning system according to the present invention;

[0030] Figure 2 This is an overall flowchart of an intelligent elderly care living assistance and monitoring early warning system according to the present invention;

[0031] Figure 3 This is a flowchart of the perception layer of an intelligent elderly care living assistance and monitoring early warning system of the present invention;

[0032] Figure 4 This is a flowchart of the output layer of an intelligent elderly care living assistance and monitoring early warning system of the present invention;

[0033] Figure 5 This is a flowchart of the intelligent processing layer of an intelligent elderly care living assistance and monitoring early warning system according to the present invention;

[0034] Figure 6 This is a flowchart of the application service layer of an intelligent elderly care living assistance and monitoring early warning system of the present invention;

[0035] Figure 7 This is a flowchart of the monitoring and early warning mechanism of an intelligent elderly care living assistance and monitoring early warning system according to the present invention;

[0036] Figure 8 This is a flowchart illustrating the hierarchical early warning response of an intelligent elderly care living assistance and monitoring early warning system according to the present invention.

[0037] The following are the labeling instructions in the diagram: 11. Environmental millimeter-wave radar; 12. Bioelectric sensor; 13. Bathroom millimeter-wave radar; 21. Gas sensor; 22. Water immersion sensor; 23. Binocular camera; 31. Service interaction terminal; 32. Voice terminal; 33. Touch terminal; 41. Intelligent walking aid; 42. Nursing bed; 43. Bathing aid; 51. Edge computing server; 52. LoRa IoT gateway; 53. Emergency backup power supply. Detailed Implementation

[0038] 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.

[0039] This invention is described in detail with reference to the schematic diagrams. When describing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not according to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0040] The orientation or positional relationship indicated in the terminology is based on the orientation or positional relationship shown in the accompanying drawings and is only for the convenience of describing the invention and simplifying the description, and is not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention.

[0041] The term "connection method" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0042] The embodiments of the present invention will now be described in further detail with reference to the accompanying drawings.

[0043] This invention provides a schematic diagram of the overall structure of an embodiment of an intelligent elderly care living assistance and monitoring early warning system, comprising:

[0044] Please see Figures 1-8 The intelligent elderly care living assistance and monitoring early warning system of this embodiment includes: a perception layer, which includes health perception nodes, safety perception nodes and interaction and assistance nodes;

[0045] The signal receiver of the transmission layer is connected to the signal output of the sensing layer;

[0046] The signal receiver of the intelligent processing layer is connected to the signal output of the transmission layer. The intelligent processing layer includes a dynamic health risk assessment engine, intelligent resource scheduling optimization, and multimodal data fusion enhancement.

[0047] The signal receiving end of the application service layer is connected to the signal output end of the intelligent processing layer. The application service layer includes the elderly end, the family end, the care end, and the management end.

[0048] The signal receiving end of the monitoring and early warning mechanism is connected to the signal output end of the intelligent processing layer. The monitoring and early warning mechanism includes graded early warning response and enhanced privacy protection.

[0049] It is worth noting that, in order to collect user data, the specific health sensing nodes include: environmental millimeter-wave radar 11, bioelectric sensor 12, and bathroom millimeter-wave radar 13. The environmental millimeter-wave radar 11 monitors breathing and heart rate, the bioelectric sensor 12 is worn on the user and collects blood pressure and blood oxygen, and the bathroom millimeter-wave radar 13 monitors bathing time.

[0050] Next, for environmental data collection, specific safety sensing nodes include: gas sensor 21, water immersion sensor 22 and binocular camera 23. The signal output terminals of gas sensor 21 and water immersion sensor 22 are connected to the signal receiving terminals of valves. The binocular camera 23 is worn by the user and is set to be activated by event triggering.

[0051] Meanwhile, to facilitate user operation, the specific interactive and auxiliary nodes include: a service interaction terminal 31 and an age-friendly device. The service interaction terminal 31 is equipped with a voice terminal 32 and a touch terminal 33. The voice terminal 32 is installed inside the service interaction terminal 31, and the touch terminal 33 can back up the collected data.

[0052] Furthermore, to assist users, the age-friendly devices specifically include: a smart walking aid 41, a nursing bed 42, and a bathing aid 43. The smart walking aid 41 is worn by the user and can avoid obstacles and cushion falls. The nursing bed 42 can assist with sleep, and the bathing aid 43 can assist with bathing.

[0053] Furthermore, for data transmission, the transmission layer specifically includes the deployment of an edge computing server 51, a LoRa IoT gateway 52, and an emergency backup power supply 53. The edge computing server 51 can locally process sensitive health data, the LoRa IoT gateway 52 can connect to sensors within a 500-meter radius, and the emergency backup power supply 53 can support continuous operation for 4 hours after a power outage. The transmission methods of the transmission layer include 5G, LoRa, and Bluetooth Mesh transmission. LoRa transmission can transmit low-frequency data, 5G transmission can transmit high-frequency health data, and Bluetooth Mesh transmission can link with local devices.

[0054] Furthermore, to assess risks, the health risk dynamic assessment engine is specifically designed based on an LSTM neural network. This engine can perform "behavioral-physiological" correlation analysis. The resource scheduling intelligent optimization improves the ant colony algorithm to a three-dimensional model of "demand priority-distance-load". This intelligent optimization supports real-time dynamic allocation of community service resources. The multimodal data fusion enhancement introduces a federated learning framework, which can protect data privacy and fuse sensor data across devices.

[0055] Furthermore, for user convenience, the elderly app features full voice interaction, the family app adds a "risk trend chart," the caregiver app supports remote setting of "safety fences," and the management app can integrate the service ticket system with the government supervision platform, with a "service quality retrospective" function.

[0056] It is worth noting that, in order to handle the early warnings, the specific tiered early warning response includes Level 1, Level 2, and Level 3 early warnings. Level 1 early warnings include minor anomalies, and after a Level 1 early warning is triggered, a voice reminder will be sent to the terminal and a silent push will be sent to the family's APP. Level 2 early warnings include potential risks, and after a Level 2 early warning is triggered, a community grid worker will be automatically dispatched to visit the family. Level 3 early warnings include emergency events, and after a Level 3 early warning is triggered, a local sound and light alarm will be triggered, the family's location will be notified, and the community emergency team will dispatch a work order.

[0057] Finally, to protect privacy, specific privacy protection enhancements include storing sensitive data locally on edge servers, transmitting only encrypted risk assessment results to the cloud, and caching camera videos locally for only 24 hours.

[0058] Example 1: The environmental millimeter-wave radar 11 deployed in the elderly's bedroom continuously monitors breathing and heart rate waveform data during sleep in a non-contact manner. The bioelectric sensor 12 worn by the elderly collects heart rate, blood oxygen saturation and single-lead ECG data during daily activities. When the elderly enter the bathroom, the bathroom millimeter-wave radar 13 is automatically activated to monitor the bathing time; the water immersion sensor 22 monitors the ground condition in real time.

[0059] Example 2: The above data is transmitted to the local edge computing server 51 via LoRa IoT gateway 52 (for low-frequency environmental data) and 5G network (for high-frequency physiological data);

[0060] Example 3: The health risk dynamic assessment engine in the edge server performs real-time analysis on the received multimodal data. It can fuse the respiratory rate waveform from the radar and the blood oxygen data from the wristband to determine whether there is a risk of sleep apnea.

[0061] Example 4: The multimodal data fusion enhancement module adopts a federated learning framework. Without exporting the original data, it uses cloud-aggregated models to optimize local algorithms and improve recognition accuracy. Once an abnormal pattern is detected, such as abnormally high heart rate, prolonged inactivity, or excessive bathing time, the engine immediately triggers an early warning mechanism.

[0062] Example 5: If the engine determines that it is a Level 3 warning (emergency event), such as detecting a severe fall (determined by fusion of radar attitude recognition and wristband accelerometer), the system will immediately trigger:

[0063] Locally: Activate the smart home's sound and light alarm to attract the attention of roommates or neighbors.

[0064] Family members: Send a strong alarm notification and emergency call to the family member's app, including the elderly person's real-time location.

[0065] Community: Automatically generate emergency work orders, dispatch them to the mobile terminals of the community emergency team, and link them with the management platform. If it is a level 2 warning (potential risk), such as detecting an abnormal increase in the number of times people get up at night for consecutive nights, the system will automatically generate a service work order, dispatch it to the community grid member, and remind them to visit the community the next day.

[0066] Example 6: All sensitive raw data (such as radar point clouds and video frames) are processed on the edge server and automatically deleted after 24 hours. Only the encrypted early warning event results and desensitized health trend data are uploaded to the cloud for long-term analysis.

[0067] Example 7: The elderly can initiate commands via the voice terminal 32 (32) of the service interaction terminal 31 (31) in daily life, such as "calling daughter" or "turning on the living room light". All interactions are mainly voice-based, with the touch terminal 33 (33) serving as an auxiliary backup.

[0068] Example 8: Family members can view the processed "risk trend map" through the family member app and remotely set up an electronic "safety fence" for the elderly.

[0069] Although the present invention has been described above with reference to embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of the invention. In particular, as long as there is no structural conflict, the features in the disclosed embodiments can be combined with each other in any manner. The lack of an exhaustive description of these combinations in this specification is merely for the sake of brevity and resource conservation. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. An intelligent elderly care living assistance and monitoring early warning system, characterized in that, It includes: a perception layer, which comprises health perception nodes, safety perception nodes, and interaction and assistance nodes; The transmission layer has a signal receiving end located at the signal output end of the sensing layer. The intelligent processing layer has its signal receiving end located at the signal output end of the transmission layer. The intelligent processing layer includes a dynamic health risk assessment engine, intelligent resource scheduling optimization, and multimodal data fusion enhancement. The application service layer has a signal receiving end located at the signal output end of the intelligent processing layer. The application service layer includes an elderly end, a family member end, a caregiver end, and a management end. A monitoring and early warning mechanism is provided, wherein the signal receiving end of the monitoring and early warning mechanism is set at the signal output end of the intelligent processing layer, and the monitoring and early warning mechanism includes graded early warning response and enhanced privacy protection.

2. The intelligent elderly care living assistance and monitoring early warning system according to claim 1, characterized in that, The health sensing nodes include: an environmental millimeter-wave radar (11), a bioelectric sensor (12), and a bathroom millimeter-wave radar (13). The environmental millimeter-wave radar (11) monitors respiratory heart rate. The bioelectric sensor (12) is installed on the user and includes blood pressure and blood oxygen acquisition. The bathroom millimeter-wave radar (13) monitors bathing time.

3. The intelligent elderly care living assistance and monitoring early warning system according to claim 2, characterized in that, The safety sensing node includes a gas sensor (21), a water immersion sensor (22), and a binocular camera (23). The signal output terminals of the gas sensor (21) and the water immersion sensor (22) are equipped with signal receiving terminals for valves. The binocular camera (23) is mounted on the user and is set to be activated by an event.

4. The intelligent elderly care living assistance and monitoring early warning system according to claim 3, characterized in that, The interaction and auxiliary nodes include: a service interaction terminal (31) and an age-friendly device. The service interaction terminal (31) is equipped with a voice terminal (32) and a touch terminal (33). The voice terminal (32) is located inside the service interaction terminal (31), and the touch terminal (33) can back up the collected data.

5. The intelligent elderly care living assistance and monitoring early warning system according to claim 4, characterized in that, The age-friendly equipment includes: a smart walking aid (41), a nursing bed (42), and a bathing aid (43). The smart walking aid (41) is installed on the user and can avoid obstacles and cushion falls. The nursing bed (42) can assist with sleep, and the bathing aid (43) can assist with bathing.

6. The intelligent elderly care living assistance and monitoring early warning system according to claim 5, characterized in that, The transmission layer includes an edge computing server (51), a LoRa IoT gateway (52), and an emergency backup power supply (53). The edge computing server (51) can process sensitive health data locally. The LoRa IoT gateway (52) can connect to sensors within a radius of 500 meters. The emergency backup power supply (53) can support continuous operation for 4 hours after a power outage. The transmission methods of the transmission layer include 5G, LoRa, and Bluetooth Mesh transmission. LoRa transmission can transmit low-frequency data, 5G transmission can transmit high-frequency health data, and Bluetooth Mesh transmission can link with local devices.

7. The intelligent elderly care living assistance and monitoring early warning system according to claim 6, characterized in that, The health risk dynamic assessment engine is set to be based on LSTM neural network. The health risk dynamic assessment engine can perform "behavior-physiology" correlation analysis. The resource scheduling intelligent optimization improved ant colony algorithm is a three-dimensional model of "demand priority-distance-load". The resource scheduling intelligent optimization supports real-time dynamic allocation of community service resources. The multimodal data fusion enhancement introduces a federated learning framework. The multimodal data fusion enhancement can protect data privacy and fuse sensor data across devices.

8. The intelligent elderly care living assistance and monitoring early warning system according to claim 7, characterized in that, The elderly user terminal can be fully voice-interactive, the family member terminal APP has added a "risk trend chart", the caregiver terminal supports remote setting of "safety fences", the management terminal can integrate the service work order system and the government supervision platform, and the management terminal has a "service quality traceability" function.

9. The intelligent elderly care living assistance and monitoring early warning system according to claim 8, characterized in that, The tiered early warning response includes Level 1, Level 2, and Level 3 early warnings. Level 1 early warnings include minor anomalies, and when triggered, a terminal voice reminder and a silent push notification to the family's APP are provided. Level 2 early warnings include potential risks, and when triggered, a community grid worker is automatically dispatched to visit the family. Level 3 early warnings include emergency events, and when triggered, a local sound and light alarm is activated, family location is notified, and the community emergency team dispatches a task.

10. The intelligent elderly care living assistance and monitoring early warning system according to claim 9, characterized in that, The enhanced privacy protection includes storing sensitive data locally on an edge server, transmitting only encrypted risk assessment results to the cloud, and caching camera videos locally for only 24 hours.

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