Automated system for the movement of at least one movable opening and closing member and method for controlling such automated system

Abstract

Automated system (1 ) for the movement of at least movable opening and closing member (3) comprising the at least one movable member (3), at least one electromechanical actuating device configured to move the at least one movable member (3) between an open position and a closed position and a central control unit (7) and / or a local control unit (6) and a cloud server, which are connected to the at least one electromechanical actuating device. The at least one electromechanical device comprises at least one electromechanical actuator (11 ) and a device for supplying electrical energy to the at least one electromechanical actuator, comprising at least one electrical energy storage device (10). The automated system (1 ) also comprises detection means configured to detect time-dependent data and / or variables relating to the operation of the at least one electromechanical actuator (11 ) and / or the at least one movable element (3) and the electrical energy supply device and at least one Internet connection device (8) configured to collect information relating to the geolocation. The invention also envisages at least one self-learning algorithm or model configured to perform the processing of the operating data and / or variables and the information relating to the geolocation and to estimate the remaining life of the at least one electrical energy storage device (10).

Description

[0001] “Automated system for the movement of at least one movable opening and closing member and method for controlling such automated system”

[0002] ★ ★★★★

[0003] Field of application

[0004] The present invention relates to an automated system for the movement of at least one movable opening and closing member such as a gate, a hinged shutter, a door, an awning or any other equivalent movable member.

[0005] The present invention also relates to a method for controlling such an automated movement system.

[0006] Prior art

[0007] Automated systems for the movement of movable opening and closing members, such as gates, hinged shutters, doors or awnings, which use electromechanical actuators, are known; said actuators may be powered autonomously by means of electrical energy which is generated by the sunlight striking one or more photovoltaic modules.

[0008] These photovoltaic modules store the energy by means of accumulators which are in turn connected in order to transfer the energy to the electromechanical actuators.

[0009] One advantage of these electromechanical actuators consists in the fact that they do not need to be connected to an electricity grid. This solution is advantageous, for example, during building renovation operations, since the installation of the aforementioned actuators does not require the laying of new electricity lines from the electric meter to the locations prechosen for installation.

[0010] Recently there has been a rapid increase in the demand for generation of electrical energy using solar power on account of its numerous advantages.

[0011] However, the use of photovoltaic modules for generating electrical energy intended for the movement of electromechanical actuators is not always reliable, unlike the power supply produced by the electricity grid.

[0012] In fact, the photovoltaic modules do not always manage to produce the electrical energy corresponding to the requirement of the electromechanical actuators, for example in the case of shading or weather conditions where there is less sunlight, or in the event of breakdown and wear.

[0013] This drawback may result in malfunctions during the movement of the movable opening and closing members.

[0014] In order to avoid the aforementioned drawback, inspections may be carried out in order to check the suitability of the site where the photovoltaic modules are to be positioned and determine whether the radiation corresponds to the energy requirement of the electromechanical actuator.

[0015] Software applications have also been developed, these being able to be installed on smartphones and configured to check the instantaneous efficiency of irradiation at the site where the photovoltaic modules are installed, for example by means of photography of the said site.

[0016] Such software analyses the photographs and establishes the suitability of the site where the photovoltaic modules will be installed in relation to the energy requirement of the movement system, in particular of the electromechanical actuators.

[0017] Such software, however, has the drawback that it does not allow precise, dynamic and predictive analysis of the operation of the movement system and the correspondence between the energy requirement of the electromechanical actuator and the electrical energy generated and stored using the photovoltaic modules.

[0018] In fact said software does not allow an evaluation of the problems relating to future climate change or variations in the energy requirement of the actuators, or a rapid response in the event of malfunctions affecting the photovoltaic modules, and / or a prediction of the programmed maintenance, and / or the provision of precise information about the real state of the movement system.

[0019] Summary of the invention

[0020] The main object of the present invention is to provide an automated system for the movement of at least one movable opening and closing member and a method for controlling such an automated system able to overcome the aforementioned drawbacks.

[0021] A further task of the present invention is to provide a system and a method of the type described above which allow the remaining life of an electrical energy storage device of the automated system to be estimated in a rapid and accurate manner.

[0022] Another task of the present invention is to provide a system and a method of the type described above which allow information regarding the remaining life of an electrical energy storage device of the system to be supplied to an operator and / or a user.

[0023] A further task of the present invention is to provide a system and a method of the type described above which allow the operation of the automated system to be regulated by a user and / or an operator depending on the estimation of the remaining life of an electrical energy storage device.

[0024] Another task of the present invention is to provide a system of the type described above which can be realized in a simple and low cost manner.

[0025] The main tasks and the object described above are achieved by an automated system for the movement of at least one movable opening and closing member in accordance with Claim 1 and by a method for controlling the automated system in accordance with Claim 11 .

[0026] Brief description of the drawings

[0027] In order to illustrate more clearly the innovative principles of the present invention and its advantages compared to the prior art, an example of embodiment of an automated system for the movement of at least one movable opening and closing member and a method for controlling such a system will be described below with the aid of the accompanying drawings. In particular:

[0028] - Figure 1 is a schematic perspective view which shows an automated system for the movement of a movable opening and closing member, such as a roll-up shutter, in accordance with a preferred embodiment of the present invention;

[0029] - Figure 2 is a side view of an electromechanical actuator of the automated movement system according to the present invention;

[0030] - Figure 3 is a block diagram in accordance with the method of the present invention for controlling the automated movement system;

[0031] - Figure 4 is a block diagram in accordance with the method of the present invention, illustrating the processing by a self-learning algorithm or model of the automated system according to the present invention;

[0032] - Figure 5 is a schematic view of a terminal which shows the predictive diagnostic values which can be obtained by means of the automated system and the method of the present invention.

[0033] Detailed description

[0034] The present invention relates to an automated system for the movement of at least one movable opening and closing member and to a method for controlling such an automated system.

[0035] In particular, the method allows a diagnosis of the electrical energy generated by means of at least one photovoltaic module and stored for the movement of at least one electromechanical actuator of the automated movement system.

[0036] Said at least one electromechanical actuator is intended in particular for the movement of movable opening and closing members, such as gates, hinged shutters, doors, awnings or any other equivalent movable member. Figure 1 shows, in a non-limiting manner, a roll-up shutter 3 as the movable opening and closing member.

[0037] The automated system according to the present invention is denoted overall by the reference number 1 in the attached figures.

[0038] In accordance with an embodiment of the present invention, the automated system 1 for the movement of at least one movable opening and closing member 3 comprises:

[0039] - at least the movable opening or closing member 3;

[0040] - at least one electromechanical actuating device configured to move the at least one movable opening and closing member 3 between an open position and a closed position;

[0041] - a central control unit 7 and / or a local control unit 6 and / or a cloud server, which are connected to the at least one electromechanical actuating device for regulating the operation thereof.

[0042] The at least one electromechanical actuating device, not shown in its entirety in the attached figures, comprises at least one electromechanical actuator 11 and a device for supplying electrical energy to the at least one electromechanical actuator 11 , said supply device comprising at least one electrical energy storage device 10.

[0043] In detail, with reference firstly to Figures 1 and 2, the automated system 1 described here may be installed in a building comprising an opening 2, for example a window or doorway, intended to be opened or closed by means of movement of the movable member 3.

[0044] The movable member 3, namely the roll-up shutter, is wound onto a horizontal roller, not visible in the attached figures, actuated by the at least one electromechanical actuator 11 , for example by a tubular motor inserted inside the said roller.

[0045] The opening and closing member 3 is movable between an open position, when it is completely wound up onto the horizontal roller, and a closed position, when it is completely unwound.

[0046] The first slat of the movable member 3, opposite to the final end slat, is connected to the horizontal roller by means of at least one joining device, in particular by means of strip-like fixing elements 5, which allow the movement of the movable member 3 by means of actuation of the at least one electromechanical actuator 11 .

[0047] The at least one electromechanical actuator 11 is configured to carry out the movement commands by means of, for example, the local control unit 6, which may be connected by means of a wired or wireless connection to the central control unit 7.

[0048] The local control unit 6 and / or the central control unit 7 is / are preferably provided with a control keyboard comprising one or more selection elements and optionally one or more display elements.

[0049] Moreover, these units 6, 7 comprise a dedicated software for controlling the at least one electromechanical actuator 11 .

[0050] Advantageously, the local control unit 6 may be a remote control device, a smartphone, a tablet or a notebook or an equivalent device.

[0051] As shown in Figure 2, the at least one electromechanical actuator 11 comprises an electric motor 13 which is operated by means of at least one electronic module 20, 40 positioned preferably in the vicinity of the electric motor 13, an epicycloidal reducer 15 and a brake 17.

[0052] The electronic module 20, 40 may also comprise a communication module for receiving the commands transmitted by the central control unit 7 and / or by the local control unit 6.

[0053] The at least one electronic module 20, 40 and / or the local control unit 6 and / or the central control unit 7 may be in communication with an external server, more particularly, with the cloud server indicated above, for generating movement commands depending on the signals received.

[0054] The at least one electrical energy storage device 10 comprises preferably at least one rechargeable battery connected to at least one photovoltaic module 9.

[0055] The rechargeable battery may comprise a plurality of electrical energy storage elements. Preferably, these electrical energy storage elements are connected in series.

[0056] The number of electrical energy storage elements of the battery is not limiting.

[0057] The electrical energy supply device, in particular, the at least one storage device 10, is configured to power electrically the at least one electromechanical actuator 11 without the need for the latter to be connected to a household power supply network. The electrical connection between the at least one electromechanical actuator 11 and the at least one electrical energy storage device 10 is preferably performed by means of at least one electric power conductor cable 14, of the type shown in Figure 2.

[0058] The at least one photovoltaic module 9 comprises at least one photovoltaic cell, preferably a plurality of photovoltaic cells. The at least one photovoltaic module 9 also comprises charging elements configured to charge the battery of the electrical energy storage device 10.

[0059] In accordance with the present invention, the automated system 1 comprises detection means, not shown in the attached figures, configured to detect timedependent data and / or variables relating to the operation of the at least one electromechanical actuator 11 and / or of the at least one movable opening and closing member 3 and the at least one electrical energy supply device.

[0060] Furthermore, the automated system 1 comprises at least one Internet connection device 8 configured to collect information relating to the geolocation of the automated system 1 . Conveniently, the means for detecting the operating data and / or variables of the at least one movable opening and closing member 3 are configured to detect the type and duration of the movement of the at least one movable member 3 when passing from the open position into the closed position and vice versa.

[0061] In particular, said detection means may detect the upward movement of the roll-up shutter 3 and its duration and / or the downward movement of the roll-up shutter 3 and its duration and / or the opening of the movable member 3 and its duration and / or the closing of the movable member 3 and its duration.

[0062] Preferably, the time value may also be monitored without the movement of the at least one electromechanical actuator 11 .

[0063] Furthermore, the means for detecting the operating data and / or variables of the at least one electromechanical actuator 11 comprise the at least one electronic module 20, 40 described above.

[0064] In this respect, the electronic module 20, 40 may be configured to control the movement of the actuator 11 and to detect the type and the number of movements of the actuator 11 with a predetermined time frequency.

[0065] Furthermore, the means for detecting the operating data and / or variables of the at least one electrical energy supply device are configured to detect the temperature of the at least one electrical energy storage device 10, namely the battery, and / or the voltage before and after the movement performed by the electromechanical actuating device and / or the electric voltage at the terminals of the at least one electrical energy storage device 10.

[0066] In this respect, the battery of the storage device 10 may comprise at least one temperature sensor, of any suitable type, and means for measuring the voltage at the terminals of the battery during the various operating phases of the system 1 .

[0067] Advantageously, further useful data and / or variables may be calculated, such as the minimum voltage value of the battery, the maximum voltage value of the battery reached, the battery percentage value corresponding to: (present battery value - minimum battery value) I (battery value available), the estimated recharging value and the time difference between the present detection time and the last recharging detection time.

[0068] These values are useful for determining beforehand any malfunctioning of the electrical energy supply device, in particular of the at least one photovoltaic module 9, for example in the case where the battery has not been charged for a period of more than two days, despite favourable weather conditions.

[0069] The connection device 8, which is typically defined as a gateway, allows access to the information stored on the web and is configured to transmit the information relating to the geolocation, typically the longitude and the latitude, of the site in which the automated system 1 with the at least one photovoltaic module 9 is installed.

[0070] The information relating to the geolocation may be transmitted to the cloud server and / or to the electronic module 20, 40 and / or to the central control unit 7 and / or to the local control unit 6, for processing by means of at least one self-learning algorithm or model, described below.

[0071] The Internet connection device 8 may also comprise a programming interface, preferably of the API type, configured to provide specific weather information intended to be correlated with the geolocation information. Said weather information may comprise, for example, the cloud coverage, the external temperature, the azimuth and the solar elevation.

[0072] The weather information may be retrieved by means of the connection on the web to site containing the weather information.

[0073] As already mentioned, at least one self-learning algorithm or model is also provided, said algorithm or model being configured to perform the processing of the time- dependent operating data and / or variables detected by the detection means and the information relating to the geolocation, as well as the weather information, and to estimate the remaining life of the at least one electrical energy storage device 10 on the basis of the processing results.

[0074] The at least one self-learning algorithm may be implemented, for example, in the central control unit 7 or in the cloud server; furthermore, the detection means and the Internet connection device 8 may be connected to the central control unit 7 for transmission of the data and / or the variable and the information to the at least one algorithm which performs the processing thereof.

[0075] The time-dependent data and / or variables relating to the at least one electromechanical actuator 11 and / or of the at least one movable opening and closing member 3 and of the electrical energy supply device represent an input for the processing operation performed by the at least one self-learning algorithm.

[0076] Furthermore, the estimate as to the remaining life of the electrical energy storage device 10, namely the battery, represents an output of the processing operation performed by means of the at least one self-learning algorithm.

[0077] Advantageously, the estimate as to the remaining life of the at least electrical energy storage device 10 may be used to alert or inform a user and / or an operator about the need for regulation of operation the automated system 1 , for example via the central control unit 7 and the local control unit 6.

[0078] Conveniently, the at least one algorithm preferably consists of an artificial intelligence model based on machine learning processes. In particular, the algorithm used is based on a decision tree model, of the type shown in Figure 4, in which the decisions are generated from the top downwards and may comprise a given series of decision trees 405. Alternatively, a neural network model may also be used.

[0079] Furthermore, the decision paths of the at least one algorithm are chosen using the criterion of minimization of the sum of the residual squares resulting from: where ynj is the forecast for the region j.

[0080] The automated system 1 may also include a database, implemented in a memory of the central control unit 7 and / or in the cloud server and comprising the operating data and / or variables and the information relating to the geolocation of the system 1 , as well as the weather information indicated above.

[0081] The at least one self-learning algorithm is configured to be trained by means of the data and / or the variables and the information of the database stored in the memory or in the server.

[0082] Therefore, the at least one self-learning algorithm uses the data and / or the variables and the information previously stored in the cloud server and / or in the central control unit 7 for determining which factors influence the energy used for the movement of the at least one electromechanical actuator 11 and estimating consequently the remaining life of the al least one storage device 10.

[0083] The central control unit 7 and / or the cloud server may also comprise an additional self-learning algorithm for processing future data regarding the operation of the at least one electromechanical actuator 11 and / or of the at least one movable opening and closing member 3 and the electrical energy supply device.

[0084] Said future data may comprise the estimated voltage conditions in the electrical energy supply device, in particular of the at least one electrical energy storage device 10, and / or the number and the type of estimated movements of the at least one electromechanical actuator 11 in the immediate future for moving the opening and closing member 3.

[0085] Moreover, on the basis of said future data it is possible to obtain a dynamic estimate as to the remaining life of the electrical energy supply device, in particular of the at least one electrical energy storage device 10, and the number of remaining movements of the at least one electromechanical actuator 11 .

[0086] Moreover, the additional algorithm may be configured to process the information relating to the future weather conditions at the site where the automated system 1 with the at least one photovoltaic module 9 is installed.

[0087] The aforementioned future data and information may be processed and estimated with a predetermined time frequency, advantageously hourly frequency.

[0088] The additional algorithm is based on an autoregressive integrated moving average model, which may be expressed by means of the following mathematical formula: y(t) = c + 4>1 * y(t-1 ) + ... + 4>p * y(t-p) + 01 * e(t-1 ) + ... + 0q * e(t-q) + $1 * y(t-s) + ... + <J>P * y(t-Ps) + 01 * e(t-s) + ... + 0Q * e(t-Qs) + (31 * x1 (t) + ... + |3n * xn(t) + s(t) where:

[0089] - y(t) represents the time series to be modelled,

[0090] - c is a constant,

[0091] - 4>1 , ..., 4>p are non-seasonal auto-regressive (AR) coefficients;

[0092] - y(t-1 ), ..., y(t-p) are the preceding values of the time series;

[0093] - 01 , ..., 0q are the coefficients of the non-seasonal moving average (MA);

[0094] - e(t-1 ), ..., e(t-q) are the preceding errors of the model;

[0095] - [31 , ..., |3n are the coefficients associated with the exogenous variables x1 (t), ..., xn(t);

[0096] - x1 (t), ..., xn(t) are the exogenous variables which may influence the time series;

[0097] - s(t) represents the residual error during the period; - <1>1 , <1>P are the coefficients of the seasonal auto-regression;

[0098] - y(t-s), y(t-Ps) are the preceding seasonal values of the time series;

[0099] - 01 , 0Q are the coefficients of the seasonal moving average;

[0100] - e(t-s), e(t-Qs) are the preceding seasonal errors of the model;

[0101] - s represents the length of the seasonal period (for example 12 for monthly data with an annual seasonal period).

[0102] The additional algorithm therefore performs the auto-regression separately for each data item and / or variable relating to the operation of the electrical energy supply device.

[0103] The automated system 1 may also comprise a mobile terminal 501 - shown schematically in Figure 5 - configured to display at least the information relating to the estimate of the remaining life of the at least one electrical energy storage device 10, obtained by means of processing by the at least one algorithm as well as further predictive diagnostic values described below.

[0104] As shown schematically in Figure 5, the at least one mobile terminal may coincide with the local control unit 6 and may consist of a smartphone 501 .

[0105] Advantageously, the information is displayed by means of a proprietary application. The application screen may display the percentage value 502 of the energy state of the storage device 10, or the battery, the estimate 503 as to the number of future movements available for the at least one electromechanical actuator 11 , the remaining working days 504 of the storage device 10, the number of days 505 from the last recharging of the storage device 10.

[0106] Furthermore, the application screen may display information 506 relating to the orientation and the operation of the at least one photovoltaic module 9. The operator or the user may also receive information about the fact that the at least one photovoltaic module 9 is not correctly installed. This latter information is estimated by means of the analysis of the recharging process of the storage device 10, considering in particular the weather information and the voltage values measured during the recharging process of the storage device 10.

[0107] Alternatively, the orientation of the at least one photovoltaic module 9 may be determined by means of a sensor, typically a gyroscope.

[0108] Furthermore, the application screen may also display text messages 507 with information relating to the diagnosis of the automated system 1 . In particular, said messages may contain information relating to malfunctioning of the photovoltaic module 9 even when there are favourable weather conditions or information regarding a less efficient performance of the storage device 10 with respect to the previous recharging operations, indicating the need for replacement thereof.

[0109] This information may be used, by a user or an operator, to regulate subsequently the operation of the automated movement system 1 .

[0110] As already mentioned, the present invention also relates to a method for controlling the automated system 1 for the movement of at least one movable opening or closing member 3 of the type described above.

[0111] Preferably, the method comprises the following steps: i) detecting time-dependent data and / or variables relating to the operation of the at least one electromechanical actuator 11 and / or the at least one movable opening and closing member 3 and the electrical energy supply device; ii) acquiring information relating to the geolocation of the automated system 1 ; iii) transmitting the data and / or the variables and / or the information to the central control unit 7 and / or to the local control unit 6 and / or to the cloud server of the automated system 1 ; iv) processing the operating data and / or the variables and / or the information relating to the geolocation of the automated system 1 by means of application of at least one self-learning algorithm or model in order to estimate the remaining life of the at least one electrical energy storage device 10.

[0112] The control method of the automated system 1 is implemented in accordance with the steps shown in the flow diagram of Figure 3.

[0113] The step i) of detecting the data and / or variables and the step ii) of acquiring the information may be performed, respectively, by the detection means and the Internet connection device 8 described above.

[0114] Before the step i), the method may also comprise a step of identification of information relating to the technical specifications of the at least one electromechanical actuator 11 and the electrical energy supply device.

[0115] In this case, the processing step iv) is performed based on said information in combination with the operating data and / or variables and the information relating to the geolocation of the automated system 1 .

[0116] Suitably, said identification step, in combination with the detection step i) and the information acquisition step ii), is represented by means of the block 301 shown in Figure 3.

[0117] The identification may be performed automatically by means of the firmware of the electronic module 20, 40 described above, after the installation of the all the components has been completed.

[0118] Alternatively, the identification step may be performed manually, namely by means of insertion by the operator of the technical specifications and / or identification codes via a mobile terminal connected to the central control unit 7 and / or to the local control unit 6 and to the cloud server.

[0119] Preferably, the technical specifications identified are sent by the firmware of the electronic module 20, 40 to the cloud server. The data and / or variables detected during step i) are transmitted, during step iii), preferably by the firmware of the electronic module 20, 40 to the cloud server, or alternatively to the central control unit 7.

[0120] As mentioned above with reference to the system 1 , the electronic module 20, 40 also acts a means for detecting the operating data and / or variables of the at least one electromechanical actuator 11 .

[0121] As mentioned, the data and / or variables may comprise the type and the duration of the movements of the at least one movable member 3 and of the at least one electromechanical actuator 11 with a predetermined time frequency and / or the voltage of the at least one electrical energy storage device 10, i.e. the battery, before the movement and after the movement of the at least one electromechanical actuator 11 , preferably after 15 minutes, as well as the energy used for the movement of the at least one electromechanical actuator 11 and the temperature of the electrical energy storage device 10. Step iii) is indicated by means of block 302 shown in Figure 3.

[0122] The information relating to the geolocation is also transmitted to the cloud server and / or to the central control unit 7; said information is used during a further step for acquisition, by means of an API programming interface, of the weather information mentioned above and intended to be correlated with the geolocation information.

[0123] Advantageously, the method comprises a step of storing the operating data and / or variables and the information relating to geolocation, as well as the weather information.

[0124] The data and / or the variables and the information are stored and memorized in the cloud server and / or in the memory of the central control unit 7 and form the database described above.

[0125] The data and / or the variables and the information are memorized with a predefined time frequency, preferably hourly frequency, and are used to train the at least one self-learning algorithm to perform the processing step iv).

[0126] Therefore, the method also comprises a step of training the at least one self-learning algorithm to perform the processing step iv) on the basis of the operating data and / or variables and the information relating to the geolocation and the weather information of the database.

[0127] The training of the at least one self-learning algorithm may be performed by carrying out a series of test movements of the at least one movable member 3 by means of the at least one electromechanical actuator 11 , detecting the operating data and / or the variables and acquiring the information relating to the geolocation and the weather information for each test movement.

[0128] Therefore, for each site in which the at least one photovoltaic module 9 is installed, it will be possible to estimate the remaining life of the at least one storage device 10 based on the operation of the at least one electromechanical actuator 11 .

[0129] During the following step, indicated by means of block 303 in Figure 3, the azimuth parameter and the corresponding solar elevation value are calculated on the basis of the information relating to the geolocation.

[0130] These variables are defined generically as additional variables and allow the values to be traced temporarily such that the at least one photovoltaic module 9 is able to recharge the storage device 10 in the event of favourable weather conditions, for example when there is zero cloud coverage with maximum solar elevation.

[0131] Block 304 in Figure 3 indicates step iv) for performing processing by means of application of the at least one self-learning algorithm or model.

[0132] With particular reference to Figure 4, the first group of data and / or variables and information is divided up into a subgroup 401 of training data 404, from which the self-learning algorithm learns the paths for formulating the forecasts, and into a subgroup 402 of test data, corresponding to the detected data, in which the forecast is compared with the detected value, resulting in a measurement of the accuracy in the forecast 403.

[0133] By means of the application of the at least one self-learning algorithm for performing the processing of the data and / or variables and information it is possible to obtain an estimate of the remaining life of the at least one electrical energy storage device 10 and a response variable relating to the forecast energy used during the movement of the at least one electromechanical actuator 11 .

[0134] There may also be provided a step for determining the data and future forecasts for operation of the at least one electrical energy supply device and the at least one electromechanical actuator 11 by means of application of an additional self-learning algorithm. This step is indicated by means of block 305 in Figure 3.

[0135] Conveniently, this step includes the creation of a second group comprising the information relating to the weather conditions and / or the electrical voltage of the electrical energy supply device and / or the number and the type of movements of the at least one electromechanical actuator 11 estimated for the immediate future in order to obtain a dynamic estimate of the remaining life of the at least one electrical energy storage device 10 and the number of available future movements of the at least one electromechanical actuator 11 based on the estimate of the remaining life of the electrical energy storage device 10.

[0136] This second group also comprises the future dates with a given frequency, advantageously hourly frequency, for estimation of the data and information.

[0137] The calculated values of the azimuth and solar elevation for the future dates are associated with this second group by means of the geolocation information acquired by the Internet connection device 8.

[0138] The time frequency of the future dates is chosen on the basis of the degree of reliability of the weather forecasts, typically five days.

[0139] The step of block 305 also comprises the determination of the variables relating to the operation of the at least one electromechanical actuator 11 for the future dates on the basis of the past behaviour of the user.

[0140] In the last final step, corresponding to step 306 in Figure 3, the remaining life of the at least one electrical energy storage device 10 and the forecast energy consumption for the future movements of the at least one electromechanical actuator 11 are estimated.

[0141] In this connection, use is made again of the at least one self-learning algorithm trained on the basis of the data and / or the variables and the information stored of the first group so that it may be applied to the future data of the second group.

[0142] In this way, an estimate of the remaining life of the at least one electrical energy storage device 10 and the forecast energy consumption for the future movements of the at least one electromechanical actuator 11 are obtained.

[0143] Advantageously, in order to obtain optimum application of the at least one trained algorithm, the two groups of data are based on the same variables.

[0144] Preferably, the energy consumption for the future movements of the electromechanical actuator 11 is calculated with a predetermined time frequency, for example hourly frequency.

[0145] During this step, the future day when the energy of the at least one electrical energy storage device 10 will fall below a minimum value designed to cause the movement of the associated electromechanical actuator 11 is determined, by interrogating the second data group where the at least one trained algorithm was applied.

[0146] In accordance with a preferred mode of implementation of the present invention, the method comprises a step of displaying the estimated value of the remaining life of the at least one electrical energy storage device 10. With reference to Figure 5 described above, the estimate as to the duration of the storage device 10 as well as the further predictive diagnostic values 502-507 described above are visible on the mobile terminal 501 .

[0147] From the above description it is now clear how the automated system and the control method according to the present invention are able to achieve advantageously the predefined objects.

[0148] In particular, as a result of the processing performed by means of the at least one self-learning algorithm of the data and / or variables detected, along with the future estimated data, the information relating to the geolocation and the weather information, it is possible to estimate the remaining life of the electrical energy storage device in a rapid and accurate manner and consequently regulate the operation of the at least one electromechanical actuator of the automated system.

[0149] Obviously, the above description of embodiments applying the innovative principles of the present invention is provided by way of example of these innovative principles and must therefore not be regarded as limiting the scope of the rights claimed herein.

Claims

Claims1. Automated system (1 ) for the movement of at least one movable opening and closing member (3), which automated system (1 ) comprises:- the at least one movable opening and closing member (3);- at least one electromechanical actuating device configured to move the at least one movable opening and closing member (3) between an open position and a closed position;- a central control unit (7) and / or a local control unit (6) and / or a cloud server, which are connected to the at least one electromechanical actuating device; wherein the at least one electromechanical actuating device comprises at least one electromechanical actuator (11 ) and a device for supplying electrical energy to the at least one electromechanical actuator (11 ) comprising at least one electrical energy storage device (10); characterized in that said automated system (1 ) comprises detection means configured to detect time-dependent data and / or variables relating to the operation of said at least one electromechanical actuator (11 ) and / or of said at least one movable opening and closing member (3) and of said electrical energy supply device and in that said automated system (1 ) comprises at least one Internet connection device (8) configured to collect information relating to the geolocation of the automated system (1 ), there being provided at least one self-learning algorithm configured to perform the processing of the operating data and / or variables and the information relating to the geolocation and to estimate the remaining life of the at least one electrical energy storage device (10).

2. System (1 ) according to the preceding claim, characterized in that the system includes at least one database implemented in a memory of said central control unit (7) and / or in said cloud server and comprising the operating data and / orvariables and the information regarding the geolocation of the system (1 ), said at least one self-learning algorithm being configured to be trained by means of said stored data and / or variables and information.

3. System (1 ) according to any one of the preceding claims, characterized in that said at least one electrical energy storage device (10) consists of at least one rechargeable battery connected to at least one photovoltaic module (9).

4. System (1 ) according to the preceding claim, characterized in that said Internet connection device (8) comprises a programming interface configured to obtain specific weather information intended to be correlated with the geolocation information, such as the cloud coverage, the external temperature, the azimuth and the elevation of the sun.

5. System (1 ) according to any one of the preceding claims, characterized in that said means for detecting the operating data and / or variables of said at least one movable opening and closing member (3) are configured to detect the type and the duration of the movement of said movable member (3) when passing from the open position to the closed position and vice versa.

6. System (1 ) according to any one of the preceding claims, characterized in that said means for detecting operating data and / or variables of said at least one electromechanical actuator (11 ) comprise an electronic module (20, 40) configured to control the movement of said at least one electromechanical actuator (11 ) and to detect the type and the number of movements of the at least one electromechanical actuator (11 ) with a predetermined time frequency.

7. System (1 ) according to any one of the preceding claims, characterized in that said means for detecting operating data and / or variables of said electrical energy supply device are configured to detect the temperature of the at least one electrical energy storage device (10) and / or the voltage before and after themovement performed by the at least one electromechanical actuator (11 ).

8. System (1 ) according to any one of Claims 5-7, characterized in that said detection means are configured to calculate further data and / or variables, such as the minimum voltage value of the electrical energy storage device (10), the maximum voltage value of the electrical energy storage device (10) reached, the percentage value of the electrical energy storage device (10) corresponding to: (present battery value - minimum battery value) I available battery value), the estimated recharging value and the time difference between the present detection time and the detection time of the last recharging operation.

9. System (1 ) according to any one of the preceding claims, characterized in that said central control unit (7) and / or the cloud server comprises an additional selflearning algorithm for processing future operating data of said at least one electromechanical actuator (11 ) and / or of said at least one movable opening and closing member (3) and of said electrical energy supply device.

10. System (1 ) according to the preceding claim, characterized in that it comprises at least one mobile terminal (501 ) configured to display at least the estimated remaining life of the at least one electrical energy storage device (10).

11. Method for controlling the operation of an automated system (1 ) for the movement of at least one movable opening or closing member (3) comprising at least one electromechanical actuating device configured to move the at least one movable opening and closing member (3) between an open position and a closed position, the at least one electromechanical actuating device comprising at least one electromechanical actuator (11 ) and a device for supplying electrical energy to the at least one electromechanical actuator (11 ) with at least one electrical energy storage device (10), which method comprises the following steps: i) detecting time-dependent data and / or variables relating to the operation ofthe at least one electromechanical actuator (11 ) and / or of the at least one movable opening and closing member (3) and of the electrical energy supply device; ii) acquiring information relating to the geolocation of said automated system (1 ); iii) transmitting the detected data and / or variables and / or the information relating to the geolocation to a central control unit (7) and / or to a local control unit (6) and / or to a cloud server of the automated system (1 ); iv) processing the operating data and / or the variables and / or the information relating to the geolocation by means of application of at least one self-learning algorithm for estimating the remaining life the at least one electrical energy storage device (10).

12. Method according to the preceding claim, characterized in that the method comprises a step of storing said operating data and / or variables and said information relating to the geolocation and a step of training said at least one self-learning algorithm on the basis of said stored operating data and / or variables and of said information relating to the geolocation in order to perform the processing step iv).

13. Method according to either one of Claims 11 -12, characterized in that the method comprises a step of identifying information relating to the technical specifications of said at least one electromechanical actuator (11 ) and of said at least one electrical energy supply device, said processing step iv) being performed on the basis of said information relating to the technical specifications in combination with said operating data and / or variables and with said information relating to the geolocation.

14. Method according to any one of Claims 11 -13, characterized in that the method comprises a step of acquiring specific weather information, such as the cloud coverage, the external temperature, the azimuth and the elevation of the sun,which are correlated with the geolocation information.

15. Method according to any one of Claims 11 -14, characterized in that the operating data and / or variables of said at least one movable opening and closing member (3) and of said at least one electromechanical actuator (11 ) comprise the type and the duration of the movement of at least one movable opening and closing member (3) when passing from the open position to the closed position and vice versa and the type and the number of movements of the at least one electromechanical actuator (11 ) with a predetermined time frequency.

16. Method according to any one of Claims 11 -15, characterized in that the operating data and / or variables relating to said electrical energy supply device comprise the voltage of the at least one electrical energy storage device (10) before and after the movement of the at least one electromechanical actuator (11 ) and the temperature of said at least one electrical energy storage device (10).

17. Method according to any one of Claims 11 -16, comprising a step of determining future operating data of said electrical energy supply device and of the at least one electromechanical actuator (11 ) by means of a further self-learning algorithm.

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