Intrusion detection system and intrusion detection method for door or window

Technical field

The present invention relates to the technical field of doors and windows, in particular to door and window detection.

Background art

As electronic technology develops, more and more users are choosing intelligent anti-theft security doors. Building upon the functions of conventional anti-theft security doors, intelligent anti-theft security doors use novel technical approaches to realize numerous intelligent functions, such as on-site audible alarm functions and remote automatic alarm functions, using an intelligent system master computer as a carrier.

In general, an intruder will use a tool such as an electric drill to damage the lock of an anti-theft security door, and thereby illegally open the door to achieve his or her illegal objectives. With regard to the means by which the intruder intrudes, accurate detection of intrusion by the intruder and the provision of an alarm are necessary.

Summary of the invention

It is hoped to provide an intrusion detection system and intrusion detection method for a door or window, which are capable of accurately detecting intrusion by an intruder, and distinguishing between intrusion by an intruder and normal use of the door.

According to one aspect, an intrusion detection method for a door or window is provided, comprising: receiving acceleration or angular velocity data acquired by a sensor attached to the door or window; judging whether multiple data samples in the acceleration or angular velocity data include consecutive data samples meeting the following predetermined criterion: (i) change amount data between every two adjacent data samples in the consecutive data samples is greater than a first predetermined threshold, and (ii) the number of data samples in the consecutive data samples is greater than a second predetermined threshold; determining whether the door or window has suffered an intrusion on the basis of the result of the judgment; and outputting the result of the determination.

According to another aspect, an intrusion detection system for a door or window is provided, comprising: a data processing unit, configured to: receive acceleration or angular velocity data acquired by a sensor attached to the door or window; and judge whether multiple data samples in the acceleration or angular velocity data include consecutive data samples meeting the following predetermined criterion: (i) change amount data between every two adjacent data samples in the consecutive data samples is greater than a first predetermined threshold, and (ii) the number of data samples in the consecutive data samples is greater than a second predetermined threshold; determine whether the door or window has suffered an intrusion on the basis of the result of the judgment; and an output unit, configured to output the result of the determination.

According to another aspect, an intrusion detection system for a door or window is provided, comprising a memory, storing a computer program instruction; and a processor, which executes the method according to the embodiments of the present disclosure when the computer program instruction is run by the processor.

According to another aspect, a machine readable storage medium is provided, storing a computer program instruction which, when run, causes a computer to execute the method according to the embodiments of the present disclosure.

According to various embodiments in the various aspects of the present disclosure, it is recognized that unlike normal usage actions such as opening/closing a door or window, when an intruder uses an electric drill or electric saw to damage a door or window, the acceleration or angular velocity data thereof has a specific form; specifically, the acceleration or angular velocity data thereof is embodied as a high-frequency continuous vibration signal. By identifying these continuous vibration signals, it is possible to identify the use of an electric drill or electric saw by an intruder to damage a door or window. Thus, according to various embodiments in the various aspects of the present disclosure, a determination is made as to whether multiple data samples in acceleration or angular velocity data include consecutive data samples meeting the following predetermined criterion: (i) change amount data between every two adjacent data samples in the consecutive data samples is greater than a first predetermined threshold, and (ii) the number of the consecutive data samples is greater than a second predetermined threshold, thereby identifying consecutive acceleration data corresponding to hole-drilling for example.

According to one embodiment in the various aspects, the following is further included: for a first data sample in the multiple data samples, receiving a second data sample in the multiple data samples, the second data sample being adjacent to the first data sample and located after the first data sample; determining change amount data between the first data sample and the second data sample; judging whether the change amount data is greater than the first predetermined threshold; if the change amount data is not greater than the first predetermined threshold, then determining count data to be 0, and determining the second data sample to be the first data sample; and if the change amount data is greater than the first predetermined threshold, then increasing the count data by 1 and judging whether the count data is greater than the second predetermined threshold; if the count data is greater than the second predetermined threshold, then judging that the multiple data samples include consecutive data samples meeting the predetermined criterion; and if the count data is not greater than the second predetermined threshold, then determining the second data sample to be the first data sample.

It is thereby possible to judge whether multiple data samples include consecutive data samples corresponding to hole-drilling.

According to one embodiment in the various aspects, the following is further included: if it is judged that the multiple data samples include the consecutive data samples meeting the predetermined criterion, generating an interrupt signal, so that the intrusion detection system enters a normal operating state from a low power consumption state. It is thereby possible to reduce the power consumption of the intrusion detection system.

According to one embodiment in the various aspects, the following is further included: acquiring multiple additional data samples in the acceleration or angular velocity data; judging whether the multiple additional data samples include consecutive data samples meeting the predetermined criterion; if it is udged that the multiple additional data samples include consecutive data samples meeting the predetermined criterion, then determining that the door or window has suffered an intrusion; and it is further possible to generate an alarm signal. It is thereby possible to accurately determine intrusion by an intruder and provide a more accurate alarm. According to one embodiment in the various aspects, the following is further included: if it is judged that the multiple additional data samples do not include consecutive data samples meeting the predetermined criterion, then determining that the door or window has not suffered an intrusion, and thereby generating a signal so that the intrusion detection system returns to the low power consumption state. It is thereby possible to further reduce the power consumption of the intrusion detection system.

Brief description of the drawings

In the drawings, embodiments are explained merely through examples, without limitation; similar reference labels in the drawings denote similar elements.

Fig. 1 shows acceleration data acquired by an acceleration sensor attached to a door or window.

Fig. 2 shows an intrusion detection method for a door or window according to an embodiment. Fig. 3 shows a method according to an embodiment for determining whether multiple data samples include consecutive data samples meeting a predetermined criterion.

Fig. 4 shows a method according to another embodiment for determining whether multiple data samples include consecutive data samples meeting a predetermined criterion.

Fig. 5 shows an intrusion detection method for a door or window according to another embodiment.

Fig. 6 shows an intrusion detection system for a door or window according to an embodiment.

Various aspects and features of various embodiments of the present invention are described with reference to the drawings mentioned above. The above drawings are merely schematic, not restrictive. Without deviating from the substance of the present invention, the sizes, shapes, labels or appearance of the elements in the above drawings may vary; they are not limited to only those shown in the drawings attached to the specification.

Detailed description of the invention

According to intrusion detection in various embodiments of the present disclosure, a sensor such as an acceleration sensor or angular velocity sensor is added to a door or window (in particular in a lock); the angular velocity sensor may be a gyroscope. Data from the sensor is processed, in order to distinguish between damage to the door or window by an intruder, and normal opening/closing of the door or window by a user and actions such as knocking the door. Damaging a door or window by an intruder is in particular using an electric drill to drill a hole in a lock of the door or window, and could also be expected to be an operation such as using an electric saw to cut through a door or window. The various embodiments below are described with reference to an intruder using an electric drill to drill a hole in a door or window, but this is not a restriction; various embodiments of the present invention could also be expected to be used in the scenario of detecting the use of an electric saw by an intruder to damage a door or window.

Normal opening/closing of a door or window by a user and actions such as knocking the door will cause corresponding changes in acceleration or angular velocity data acquired by the sensor; however, compared with the use of an electric drill by an intruder to drill a hole in the door or window, the acceleration or angular velocity data corresponding to normal opening/closing of the door or window and actions such as knocking the door have a different form. Fig. 1 shows acceleration data acquired by an acceleration sensor attached to a door or window, wherein acceleration data corresponding to each axis in a three-axis acceleration sensor is shown separately; the horizontal axis represents time, and the vertical axis represents the values of acceleration data for the various axes. In Fig. 1, part A corresponds to an action of opening/closing a door or window by a user, part B corresponds to an action of using an electric drill to drill a hole in a door or window, and part C corresponds to an action of a door or window striking a door frame/window frame. As can be seen from Fig. 1, the acceleration data corresponding to the action of drilling a hole is obviously different from the acceleration data corresponding to the normal opening/closing and striking actions of the door or window, being manifested as a high-frequency continuous vibration signal corresponding to a single hole-drilling action, and there are multiple continuous vibration signals corresponding to multiple hole-drilling actions. Although not shown the corresponding angular velocity data is also embodied as a similar continuous vibration signal.

With regard to the abovementioned features of the hole-drilling action, various embodiments of the present disclosure determine whether multiple data samples in acceleration or angular velocity data include consecutive data samples meeting a predetermined criterion, wherein the predetermined criterion includes

(i) change amount data between every two adjacent data samples in the consecutive data samples being greater than a first predetermined threshold, and

(ii) the number of the consecutive data samples being greater than a second predetermined threshold. The consecutive data samples are as shown by part D in Fig. 1, and correspond to a single hole-drilling.

Fig. 2 shows an intrusion detection method 1000 for a door or window according to an embodiment. A description is given below with reference to the use of an acceleration sensor to measure acceleration data. Acceleration data can also be replaced by angular velocity data to achieve the same functions and objectives.

According to the intrusion detection method 1000, acceleration data acquired by an acceleration sensor attached to a door or window (in particular in a lock) is received in step 1100. The acceleration sensor may be a three-axis acceleration sensor, and the acceleration data comprises acceleration data corresponding to at least one axis in the three-axis acceleration sensor. In one embodiment, the following processing can be carried out for the acceleration data of each axis respectively.

In one embodiment, the acceleration sensor has a predetermined output data bandwidth, e.g. an output data bandwidth greater than or equal to 100 Hz, preferably an output data bandwidth greater than or equal to 200 Hz, in order to detect a high-frequency vibration signal corresponding to a hole-drilling action. According to Shannon’s theorem, when the output data bandwidth of the acceleration sensor is greater than or equal to 200 Hz, the output data rate of the acceleration sensor is greater than or equal to 400 Hz. The acceleration data acquired by the acceleration sensor comprises data samples acquired at a predetermined output data rate.

When an angular velocity sensor is used, the angular velocity sensor may also be a three-axis angular velocity sensor, and the angular velocity data comprises angular velocity data corresponding to at least one axis in the three- axis angular velocity sensor. Similarly, the following processing can be carried out for the angular velocity data of each axis respectively. The angular velocity sensor may similarly have the predetermined output data bandwidth mentioned above. In step 1200, for multiple data samples in the acceleration data, a judgment is made as to whether the multiple data samples include consecutive data samples meeting the following predetermined criterion: (i) change amount data between every two adjacent data samples in the consecutive data samples is greater than a first predetermined threshold, and (ii) the number of the consecutive data samples is greater than a second predetermined threshold, so as to determine whether the multiple data samples include consecutive data samples corresponding to a hole drilling action. Thus, a determination is made as to whether the door or window has suffered an intrusion on the basis of the judgment result. The first and second predetermined thresholds are set manually for multiple data samples; preferably, the first predetermined threshold is in the range of 8 - 10 mg, and the second predetermined threshold is in the range of 70 - 150 mg.

In one embodiment, the multiple data samples are acquired at a predetermined output data rate by the acceleration sensor as described above.

In another embodiment, the multiple data samples are obtained by sampling the acceleration data according to a predetermined rule. For example, the multiple data samples are extracted from the acceleration data at a predetermined sampling rate. Data samples for angular velocity data may also be obtained by sampling in this way.

In step 1300, a determination result relating to door or window intrusion is outputted. In one embodiment, if it is judged in step 1200 that the multiple data samples include consecutive data samples meeting the predetermined criterion mentioned above, this indicates that a hole-drilling action has been discovered, and it is thereby possible to determine that intrusion has taken place, in which case, in step 1300, the result of the determination is outputted to indicate that intrusion has taken place; otherwise, the result of the determination is outputted to indicate that no intrusion has been discovered.

In a further embodiment, in step 1200, in response to the result of the judgment indicating that the multiple data samples include consecutive data samples meeting the predetermined criterion mentioned above, an interrupt signal is further generated and outputted to a microcontroller unit of the intrusion detection system, so that the intrusion detection system, which was originally in a low power consumption state, enters a normal operating state from the low power consumption state. For example, in the normal operating state, data samples can be extracted at a second sampling rate, which is higher than a first sampling rate in the state of lower power consumption.

In one embodiment, based on the determination result generated in step 1300 indicating that intrusion has taken place, an alarm signal can be generated, so that an alarm device issues an alarm.

In another embodiment, it could be expected that in step 1200 a judgment be made as to whether multiple data samples of a predetermined time period include two or more consecutive data samples meeting the predetermined criterion mentioned above, i.e. a judgment is made as to whether two or more hole-drilling actions have been discovered. In response to a judgment in step 1200 that two or more hole-drilling actions have been discovered, it is determined that the door or window has suffered an intrusion. In step 1300, an alarm signal is generated in response to the result of the determination, so that the alarm device issues an alarm, and the result of the determination is thereby outputted.

Fig. 3 shows a method according to an embodiment for judging whether multiple data samples include consecutive data samples meeting a predetermined criterion, i.e. the processing carried out in step 1200 above is shown. According to the method 1200, in step 1205, n is set to 1, and i is set to 0, wherein n is a sequence number of a data sample, and i is count data. In step 1210, an nth data sample is acquired. In step 1215, an (n+l)th data sample is acquired. In step 1220, change amount data between the nth data sample and the (n+l)th data sample is determined, for example slope_a(n+l)=a(n+l)-a(n), wherein a(n) denotes the nth data sample. In the case where acceleration data for each axis of a three-axis acceleration sensor is used for detection, the change amount data can be determined for data samples of each axis. For example, slope_x(n+ 1 )=x(n+ 1 )-x(n), slope_y(n+ 1 )=y(n+ 1 )-y(n), slope_z(n+ 1 )=z(n+ 1 )-z(n), wherein x(n), y(n) and z(n) are data samples corresponding to each axis of the three-axis acceleration sensor respectively, and slope_x(n+l), slope_y(n+l) and slope_z(n+l) are change amount data between adjacent data samples for the three axes of the acceleration sensor respectively. The same is true for a three-axis angular velocity sensor.

The calculation of change amount data described above is not restrictive; another method could also be used to calculate change amount data between adjacent data samples, as long as the change amount data can indicate change between adjacent data samples.

In step 1225, a judgment is made as to whether the change amount data obtained in step 1220 is greater than a first predetermined threshold, wherein the first predetermined threshold indicates a condition that should be met by the change amount data between adjacent data samples. If it is judged in step 1225 that the change amount data between the nth and (n+l)th data samples is not greater than the first predetermined threshold, then the method advances to step 1230, in which n is set to n+1 and the count data i is zeroed, and the method then returns to step 1215, in which the next data sample, i.e. a new (n+l)th sample, is acquired.

If it is judged in step 1225 that the change amount data between the nth and (n+l)th data samples is greater than the first predetermined threshold, then the method advances to step 1235, in which the count data i is increased by 1, i.e. i=i+l . The method then advances to step 1240, in which a judgment is made as to whether the count data i is greater than a second predetermined threshold; if the count data i is greater than the second predetermined threshold, this indicates that the number of consecutive data samples, for which the change amount data of adjacent data samples therein is greater than the first predetermined threshold, is greater than the second predetermined threshold. This indicates that consecutive data samples corresponding to a single hole-drilling have been detected, in which case, in step 1250, a determination is made as to whether intrusion has taken place on the basis of the judgment result; in one embodiment, it can be determined that intrusion has taken place when consecutive data samples corresponding to a single hole-drilling have been detected.

If it is judged in step 1240 that the count data i is not greater than the second predetermined threshold, then the method advances to step 1260, in which n is set to n+1, and the method then returns to step 1215, in which an (n+l)th sample is acquired.

Referring to the embodiment shown in Fig. 3 as above, at the same time as data samples are received in sequence, it is possible to determine whether multiple received data samples include consecutive data samples corresponding to a single hole-drilling. When there are data samples x(n), y(n) and z(n) corresponding to each axis of a three-axis sensor respectively, it could be expected that the process described above be carried out for data samples of each axis respectively; as long as it is detected that data samples of at least one of the axes include consecutive data samples meeting the predetermined criterion mentioned above, a determination result is generated that consecutive data samples corresponding to a single hole-drilling have been detected.

The processing in step 1200 has been described above for nth and (n+l)th data samples, but it could also expected that a first data sample and a second data sample be used to replace the nth data sample and (n+l)th data sample; it is merely the manner of description that is different. “First” and “second” do not indicate sequence positions in multiple data samples. In this case, in step 1210, for multiple data samples, a first data sample is acquired. In step 1215, for the first data sample, a second data sample in the multiple data samples is received, the second data sample being adjacent to the first data sample and located after the first data sample. In step 1220, change amount data between the first data sample and second data sample is determined. In step 1225, a judgment is made as to whether the change amount data between the first data sample and second data sample is greater than a first predetermined threshold. If it is determined that the change amount data is not greater than the first predetermined threshold, then in step 1230, the count data i is zeroed; and the current second data sample is determined as being the first data sample, and the method then returns to 1215 to receive the next second data sample.

If it is judged in step 1225 that the change amount data is greater than the first predetermined threshold, then in step 1235, the count data i is increased by 1 and then in step 1240, a judgment is made as to whether the count data is greater than a second predetermined threshold; if the count data is greater than the second predetermined threshold, then in step 1250, a determination is made as to whether intrusion has taken place on the basis of the judgment result. If it is judged in step 1240 that the count data is not greater than the second predetermined threshold, then in step 1260, the second data sample is determined as being the first data sample, and the method then returns to step 1215 to receive the next second data sample.

The method 1200 for determining whether multiple data samples include consecutive data samples corresponding to a single hole-drilling has been described above with reference to Fig. 3. Unlike Fig. 3, Fig. 4 shows a method 1200’ according to another embodiment for determining whether multiple data samples include consecutive data samples meeting a predetermined criterion. Building upon the method 1200 shown in Fig. 3, Fig. 4 shows a scenario in which, for data samples of a predetermined time period, a determination is made as to whether they include one or more sets of consecutive data samples corresponding to one or more hole-drillings respectively. According to the method 1200’ shown in Fig. 4, in step 1205, a consecutive data sample set counter j is additionally established, and an initial value of j is set to 0; in step 1225, it is judged that the change amount data is not greater than the first predetermined threshold, the method advances to step 1227, and a determination is made in step 1227 as to whether n is less than the total number of multiple data samples of the predetermined time period; if it is smaller, then the method advances to step 1230, but if it is not smaller, then the method advances to step 1228; and a determination is made as to whether intrusion has taken place on the basis of all of the judgment results, e.g. a determination can be made as to whether intrusion has taken place with reference to the value of the counter j. Preferably, it is determined that intrusion has occurred when j is greater than 1. If it is judged in step 1240 that the count data i is not greater than the second predetermined threshold, the method advances to step 1255; in step 1255, just like in step 1227, a determination is made as to whether n is less than the total number of multiple data samples of the predetermined time period; if it is smaller, then the method advances to step 1260, but if it is not smaller, then the method advances to 1265; just like in step 1228, the value of the counter j is outputted, and a judgment is made as to whether intrusion has taken place. Additionally, according to the method 1200’ shown in Fig. 4, in step 1250, it is not judged that intrusion has taken place, but merely indicated that data corresponding to a single hole-drilling has been detected, and j is increased by 1, i.e. j=j+l, and the method then advances to step 1227.

Referring to the embodiment shown in Fig. 4, it is possible to determine consecutive data samples corresponding to how many hole-drillings are included in multiple acceleration sample data of a predetermined time period. The embodiment shown in Fig. 4 can be further improved, so that after the counter j has been updated in step 1250, a determination is made as to whether the value of j is greater than a third predetermined threshold, e.g. 1; if it is greater than 1, then regardless of whether detection has already been completed for the whole of the predetermined time period, the method advances directly to step 1228 and it is determined that intrusion has taken place, and an alarm can then be issued according to the determination result. Preferably, an alarm is issued only if two sets of consecutive data samples corresponding to at least two hole-drillings are detected within a predetermined time period of 2 seconds for example. The accuracy of alarms is thereby improved.

As described above with reference to Fig. 4, an alarm can be issued directly if it is detected that multiple data samples of a predetermined time period include two or more sets of consecutive acceleration data meeting a predetermined criterion.

Unlike the scenario in which an alarm is issued directly, in some embodiments, the intrusion detection system might initially be in a low power consumption state, in which acceleration data is sampled at a relatively low sampling rate for example; if data samples corresponding to hole-drilling are discovered, then an interrupt can be issued so that the intrusion detection system returns to a normal operating state, in which acceleration data is sampled at a relatively high sampling rate. In the normal operating state, it is possible to further determine whether data samples include data samples corresponding to hole drilling, and if they do, an alarm is issued. According to these embodiments, the accuracy of alarms can be ensured while reducing power consumption, thus avoiding false positive alarms.

Fig. 5 shows an intrusion detection method 2000 for a door or window according to these embodiments. In step 2100, multiple data samples in acceleration or angular velocity data from a sensor are acquired. When the sensor acquires the data, the intrusion detection system is operating in a low power consumption mode, e.g. a microcontroller or Bluetooth, etc. is in an idle mode or low power consumption mode, but the sensor remains able to acquire sensor data of the door or window. In this case, acceleration or angular velocity data can be sampled at a relatively low first sampling rate, so as to obtain multiple data samples. As described below, a sampling unit included in a data processing unit can be used to carry out sampling of the acceleration or angular velocity data.

In step 2200, a judgment is made as to whether the multiple data samples include consecutive data samples meeting a predetermined criterion; in a preferred embodiment, this can be achieved by the processing method 1200 as shown in Fig. 3. If it is judged in step 2200 that the multiple data samples do not include consecutive data samples meeting the predetermined criterion, then the method returns to step 2100, to continue the acquisition of data samples with the intrusion detection system operating in the low power consumption mode. If it is judged in step 2200 that the multiple data samples include consecutive data samples meeting the predetermined criterion, then in step 2300, an interrupt signal is generated and issued, so that the intrusion detection system enters the normal operating mode. Moreover, in one embodiment, in the normal operating mode, acceleration data can be sampled at a relatively high second sampling rate, in order to acquire multiple additional data samples.

In step 2400, a judgment is made as to whether the multiple additional data samples include consecutive data samples meeting the predetermined criterion; in a preferred embodiment, this can be achieved by the processing method 1200’ as shown in Fig. 4, e.g. a determination is made as to whether two or more sets of consecutive acceleration data are included in a predetermined time period of 2 seconds. If it is judged in step 2400 that the multiple additional data samples do not include consecutive data samples meeting the predetermined criterion, then the method can return to step 2100, telling the intrusion detection system to return to the low power consumption mode for operation, and continuing to sample acceleration data at the first sampling rate for example, with the intrusion detection system operating in the low power consumption mode. If it is judged in step 2400 that the multiple additional data samples include consecutive data samples meeting the predetermined criterion, then in step 2500, it is further judged that intrusion has taken place on the basis of the judgment result of step 2400, and a alarm signal is generated so that an alarm device issues an alarm. Then in step 2600, acceleration or angular velocity data is further acquired and a judgment is made as to whether multiple data samples of the further acquired acceleration or angular velocity data include consecutive data samples meeting a predetermined criterion; if so, then the method returns to step 2500 to issue a further alarm, otherwise the method returns to step 2100 such that the intrusion detection system returns to the low power consumption mode. In a preferred embodiment, the processing method 1200’ as shown in Fig. 4 can determine whether consecutive acceleration or angular velocity data samples corresponding to hole-drilling are present within a predetermined time (e.g. 1 minute); if they are present, then the method returns to step 2500 to issue a further alarm, otherwise the method returns to step 2100.

It can be understood that the processing in steps 2200, 2400 and 2600 above can be realized by the method as shown in either Fig. 3 or Fig. 4. Furthermore, the sampling of acceleration or angular velocity data can be achieved by a corresponding sampling unit.

Although the intrusion detection method for a door or window has been described above with reference to the different embodiments shown in Figs. 2 - 5, these embodiments are not restrictive, and can be combined to obtain different results. Moreover, the various processing operations and method steps mentioned above are not restrictive, and can be merged/combined/altered/amended to acquire corresponding results. Furthermore, as long as the essence of the technical solution of the present invention is not departed from, the order of the various processing operations can be suitably adjusted.

The abovementioned first predetermined threshold, second predetermined threshold, third predetermined threshold, first sampling rate, second sampling rate and predetermined time period can be set manually according to experience, and in particular set differently for different scenarios; for example, the first predetermined threshold, second predetermined threshold and third predetermined threshold may be different in a scenario in which an electric drill is used to drill a hole and a scenario in which an electric saw is used to cut a door or window. In addition, for different data samples, the first predetermined threshold and second predetermined threshold can change accordingly. For example, different first predetermined thresholds and second predetermined thresholds are used for data samples acquired at a low sampling rate or output data rate and data samples acquired at a high sampling rate or output data rate respectively.

Fig. 6 shows an intrusion detection system 100 for a door or window according to an embodiment. As shown in Fig. 6, the intrusion detection system 100 at least comprises a data processing unit 40 and an output unit 50; the data processing unit 40 can carry out the various processing operations described above with reference to Figs. 2 - 4. The output unit 50 can output a determination result of the data processing unit 40.

In the embodiment shown in Fig. 6, the intrusion detection system 100 may further comprise a sensor 20, which may be an acceleration sensor or an angular velocity sensor, and is preferably a three-axis sensor. The sensor 20 is attached to a door lock 10, in order to acquire acceleration or angular velocity data of a door or window. The acquired sensor data can be transmitted via a network 30 to the data processing unit 40 for further processing. In one embodiment, the data processing unit 40 further comprises a sampling unit (not shown), for sampling sensor data according to a predetermined rule.

In a further preferred embodiment, the intrusion detection system 100 further comprises an alarm unit (not shown), which receives a determination result from the output unit 50 indicating that multiple data samples include consecutive data samples corresponding to hole-drilling, and correspondingly generates an alarm signal, to induce an alarm device (such as a microphone, not shown) to issue an alarm. The alarm device can be disposed on the door or window, or can be disposed in a remote monitoring position, and receive the alarm signal from the alarm unit via the network 30.

Fig. 6 shows an instance in which the data processing unit 40 and output unit 50 are not disposed on the door or window; it could also be expected that the data processing unit 40 and output unit 50 be disposed on the door or window. In this embodiment, the alarm unit and alarm device may be located in remote positions, and receive a determination result from the output unit 50 via the network. As can be expected, the various units of the intrusion detection system 100 in various embodiments of the present disclosure can be disposed on the door or window or in remote positions according to requirements.

The operation of the intrusion detection system 100 as shown in Fig. 6 is described below with reference to the intrusion detection method shown in Fig. 5 alone; the processing shown in Figs. 2 - 4 is not referred to again superfluously. According to the embodiment shown in Fig. 5, in step 2100, the data processing unit 40 acquires multiple data samples in acceleration or angular velocity data from the sensor. This can be acquired by means of the sampling unit. When the sensor acquires the acceleration or angular velocity data, the intrusion detection system is operating in a low power consumption mode.

In step 2200, the data processing unit 40 judges whether the multiple data samples include consecutive data samples meeting a predetermined criterion. If it is determined in step 2200 that the multiple data samples do not include consecutive data samples meeting the predetermined criterion, then the method returns to step 2100, to continue the acquisition of data samples with the intrusion detection system operating in the low power consumption mode. If it is judged in step 2200 that the multiple data samples include consecutive data samples meeting the predetermined criterion, the data processing unit 40 determines that potential intrusion has taken place, and in step 2300, the data processing unit 40 generates an interrupt signal and sends same to a microcontroller of the intrusion detection system via the output unit 50, so that the intrusion detection system enters the normal operating mode. At the same time, the data processing unit 40 acquires multiple additional data samples.

In step 2400, the data processing unit 40 judges whether the multiple additional data samples include consecutive data samples meeting the predetermined criterion. If it is judged in step 2400 that the multiple additional data samples do not include consecutive data samples meeting the predetermined criterion, then the method can return to step 2100, telling the intrusion detection system via the output unit 50 to return to operation in the low power consumption mode, and continuing to sample acceleration or angular velocity data with the intrusion detection system operating in the low power consumption mode. If it is judged in step 2400 that the multiple additional data samples include consecutive data samples meeting the predetermined criterion, then in step 2500, it is determined that intrusion has taken place, thus a determination result of the alarm unit from the data processing unit generates an alarm signal so that the alarm device issues an alarm. Then in step 2600, the data processing unit 40 further acquires data samples and judges whether the further acquired data samples include consecutive data samples meeting a predetermined criterion; if so, then the method returns to step 2500 and the determination that intrusion has taken place is upheld, and a further alarm is issued, otherwise the method returns to step 2100, telling the intrusion detection system via the output unit 50 to return to the low power consumption mode.

Although the functions of the data processing unit 40, the output unit 50 and the alarm unit have not been described with reference to all of the processing in Figs. 2 - 5, those skilled in the art can imagine how to design the functions of the data processing unit 40, the output unit 50 and the alarm unit in order to realize the various processing operations in the intrusion detection method according to various embodiments of the present disclosure.

The intrusion detection method for a door or window has been described above with reference to the embodiments of Figs. 2 - 5, and the intrusion detection system for a door or window has been described in detail with reference to the embodiment of Fig. 6; these embodiments can be combined to obtain different results, with no restriction on the subject matter type. Moreover, the various units/processing operations mentioned above are not restrictive, and the functions of the various units/processing operations mentioned above can be merged/combined/altered/amended to acquire corresponding results. The functions of these units can be realized by software or corresponding hardware, or the functions of the various units mentioned above can be realized by means of a processor, e.g. the processor can read computer programs in a memory, and run these computer programs to realize the functions of the various units mentioned above. Specifically, the functions of the data processing unit mentioned above can be realized in a microcontroller of an intelligent lock for a door or window.

As will be understood, the intrusion detection system and method in the embodiments of the present disclosure may be realized by a computer program/software. This software may be loaded into an operating memory of a data processor, and when run, is configured to execute the method according to the embodiments of the present disclosure.

Demonstrative embodiments of the present disclosure cover both of the following: creating/using the computer program/software of the present disclosure from the start, and switching an existing program/software to use of the computer program/software of the present disclosure by means of an update.

According to another embodiment of the present disclosure, a machine (e.g. computer) readable medium is provided, for example a CD-ROM, wherein the readable medium has computer program code stored thereon; when executed, the computer program code causes a computer or processor to execute the method according to the embodiments of the present disclosure. The machine-readable medium is for example an optical storage medium or solid-state medium supplied with other hardware or as part of other hardware.

The computer program for executing the method according to the embodiments of the present disclosure may also be issued in another form, e.g. via the internet or another wired or wireless telecommunication system.

The computer program may also be provided on a network such as the world wide web, and can be downloaded from such a network into a working computer of a data processor.

It must be pointed out that the embodiments of the present disclosure are described with reference to different subject matters. In particular, some embodiments are described with reference to method-type claims, whereas other embodiments are described with reference to device-type claims. However, those skilled in the art will know from the descriptions above and below that unless otherwise specified, besides any combination of features of one type of subject matter, any combination of features relating to different subject matters are also regarded as being disclosed in the present application. Furthermore, it is possible to combine all features, to provide a synergistic effect greater than the simple sum of features.

Specific embodiments of the present disclosure have been described above. Other embodiments are within the scope of the attached claims. In some cases, actions or steps recorded in the claims may be executed in a different order from that in the embodiments but still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require to be performed in the specific order or consecutive order shown in order to achieve the desired result. In some embodiments, multi-task processing and parallel processing are also possible or possibly advantageous.

The present disclosure has been described above with reference to specific embodiments; those skilled in the art should understand that the technical solution of the present disclosure may be realized in various ways without departing from the spirit and basic features of the present disclosure. Particular embodiments are merely schematic, not restrictive. Furthermore, these embodiments may be combined at will to achieve the object of the present disclosure. The scope of protection of the present disclosure is defined by the attached claims.

The word “comprises” in the specification and claims does not rule out the existence of other elements or steps; expressions such as “first” and “second” do not indicate order, and do not define quantity. The functions of the elements described in the specification or recorded in the claims may also be split up or combined, and realized by corresponding multiple elements or a single element.