Patent Description:
<CIT> discloses systems and methods for providing animal information related to at least one animal which may sense, with at least one sensor of at least one device on the animal or in the animal's environment, information related to the animal. At least one device processor may automatically transform the sensed information into descriptive information describing a condition of the animal or related to the animal. The at least one device processor and/or at least one remote processor in communication with the at least one device processor may compare the descriptive information to known information relevant to the condition. The at least one device processor and/or at least one mobile device in communication with the at least one device processor may report information about the animal utilizing the descriptive information and the database information. The at least one device processor and/or the at least one remote processor may also generate a personalized recommendation related to the animal using the descriptive information and at least one of the known information and information related to the animal provided by a user.

Besides, document <CIT>, according to its abstract, relates to systems and methods for remote interaction with animals, focused on web-enabled devices that are worn by animals, such as domestic pets, and that are configured to communicate with a remote server in the context of a communications framework, thereby facilitating interactions. The nature of interaction includes location monitoring, owner-pet communication, pet-owner communication, and interaction via other networked devices.

Document <CIT>, according to its abstract, relates to systems for containing, training, and tracking pets utilizing electronic pet tags or collars, including IR reception and two-way RF communication. An aimable IR directional zone defining unit includes selectable different modes of operation relative to a pet collar or tag. A RF base station arranged to communicate with a pet collar or tar is arranged to automatically communicate with at least one terminal responsive to a receipt of a RF signal indicative of at least one of: condition of the pet, behavior of the pet, and proximity of the pet to the base station. The base station may further generate a user-perceptible alarm signal. A handheld remote controller adapted to communicate with the electronic pet collar or tag includes memory for digital media files, and an audio output element to deliver audible pet training instructions from the memory element.

One object of the present disclosure is to propose a method for monitoring animals which enables fine monitoring of animals with an autonomous monitoring device having low energy consumption.

To this end, the present disclosure proposes a method for monitoring at least one animal with an autonomous monitoring device being in close proximity to the animal, said monitoring device having at least a processor, a first sensor communicating with the processor and having a first electric power consumption, a second sensor communicating with the processor and having a second electric power consumption, said first electric power consumption being lower than the second electric power consumption, and a battery feeding at least said processor, first sensor and second sensor,.

Thanks to these dispositions, fine monitoring of the animal is achieved due to cross-determination by the first and second sensors, without impairing the autonomy of the monitoring device since only the low consumption first sensor is activated permanently.

In embodiments of the above method, one may further use one or several of the following features and any combination thereof:.

Another object of the present disclosure is a system for monitoring at least one animal, said system including an autonomous monitoring device adapted to be in close proximity to the animal, said monitoring device having at least a processor, a first sensor communicating with the processor and having a first electric power consumption, a second sensor communicating with the processor and having a second electric power consumption,.

In embodiments of the above system, one may further use one or several of the following features and any combination thereof:.

Other features and advantages will appear from the following description of three embodiments, given by way of non-limiting examples, with regard to the drawings.

In the various drawings, the same references designate identical or similar elements.

<FIG> illustrates a system according to a first embodiment of the present disclosure for monitoring at least one animal <NUM>.

The animal <NUM> shown on <FIG> is a dog, but the disclosure is not limited to use of the system with dogs. On the contrary, the disclosure is applicable to animals in general, although some embodiments of the disclosure may be specifically intended for dogs.

The system of <FIG> includes an autonomous monitoring device <NUM> being in close proximity to the animal <NUM>. When the animal <NUM> is big enough, the monitoring device <NUM> may be worn by the animal <NUM>. For instance, the animal <NUM> may have a collar <NUM> around its neck and the monitoring device <NUM> may be attached to said collar <NUM>. Similarly, the monitoring device <NUM> may be attached to a harness or similar worn by the animal <NUM>.

The monitoring device <NUM> may communicate through a network <NUM> (N) with a server <NUM> (S), and the server <NUM> may communicate with a mobile device <NUM> such as a smartphone or similar of a user, through the network <NUM> or through another network <NUM>.

Alternatively, the monitoring device <NUM> may communicate directly with the mobile device <NUM> through the network <NUM>. In this case, the server <NUM> might in some cases be omitted.

The network <NUM> may be any known network, for instance the network <NUM> may be or include a WAN such as the internet. Access to the network <NUM> may be done in any known way, for instance by radio communication using <NUM>, <NUM>, <NUM> or <NUM> protocol, or by a wired communication, or by a LAN (for instance a radio LAN using Wi-Fi, Bluetooth®, LORA®, SigFox® or NBIoT protocol) combined with one of a radio communication using <NUM>, <NUM>, <NUM> or <NUM> protocol and a wired communication. Typically, the monitoring device <NUM> may communicate with the network <NUM> using a radio LPWAN (Low Power Wide Area Network) connection such as for instance LORA®, SigFox® or NBIoT, the at least one server <NUM> may communicate with the network <NUM> by wired connection and the mobile <NUM> may communicate with the network <NUM> by a <NUM>, <NUM>, <NUM> or <NUM> connection and / or by a WIFI connection.

As shown in <FIG>, the monitoring device <NUM> may have:.

The monitoring device <NUM> may further include at least one telecommunication interface <NUM>-<NUM> communicating with the processor <NUM>, for instance a radio LPWAN (Low Power Wide Area Network) interface <NUM> (LP E/R) and a radio LAN (Local Area Network) interface <NUM> (WIFI). The LPWAN interface <NUM> may be for instance a LORA®, SigFox® or NBIoT interface, and the LAN interface <NUM> may be for instance a WIFI interface or a BLUETOOTH® interface. The LAN interface may communicate with a router or gateway 15a, which may for instance be located inside a building <NUM> in which the animal is normally hosted.

In the particular embodiment of <FIG>, the above mentioned sensors may include:.

The monitoring device <NUM> may include more sensors than the above, and some of the above sensors may be omitted in some embodiments.

The system may use an artificial intelligence to interpret data from the sensors. Such artificial intelligence may be in the form of a neural network <NUM>, 9a (NN). Such neural network <NUM> may be embedded in and run on the processor <NUM> as shown in <FIG>. Alternatively, the neural network 9a may be run on the at least one server <NUM> (<FIG>).

When operating the system, the processor <NUM> is configured to have a first parameter measured by the first sensor (hence with low power consumption) while the second sensor is deactivated. An estimated status of the animal is then determined by the system (more particularly, by the processor <NUM> or the server <NUM>) based on the first parameter. The estimated status may be determined by the artificial intelligence of the system, which is trained in this purpose. More particularly, the estimated status may be determined locally on the processor <NUM> by the neural network <NUM> and / or at the server <NUM> by the neural network 9a. The estimated status may be sent to the user on his or her mobile device <NUM>.

If said estimated status corresponds to at least one predetermined status, the processor <NUM> is configured to activate the second sensor and to measure a second parameter with said second sensor. Such activation may be either automatic and based on the estimated status, or triggered by the user from the mobile device <NUM>.

A specified estimated status of the animal is then determined by the system (more particularly, by the processor <NUM> or the server <NUM>) based on the second parameter, to more precisely determine the situation of the animal <NUM>. The specified estimated status may be sent to the user on his or her mobile device <NUM>. The specified estimated status may be determined by the artificial intelligence of the system, which is trained in this purpose. More particularly, the specified estimated status may be determined locally on the processor <NUM> by the neural network <NUM> and / or at the server <NUM> by the neural network 9a.

Three examples of use of the monitoring device <NUM> will now be described.

In a first example, as illustrated on <FIG> and not part of the claimed subject matter, the first sensor may be the accelerometer <NUM> and the second sensor may be the microphone <NUM>. The first parameter is thus acceleration and the second parameter is sound captured by the microphone <NUM>. This first example may be suited in particular when the animal <NUM> is a dog and wears the monitoring device <NUM>.

At step <NUM>, the processor <NUM> detects movement by the accelerometer <NUM>. This step <NUM> may be implemented continuously or very frequently without limiting the autonomy of the monitoring device <NUM>, since the accelerometer consumes extremely low electric power. At step <NUM>, the microphone <NUM> and other power-consuming sensors of the monitoring device <NUM> are off.

At step <NUM>, the movement or activity of the dog may be recognized by the neural network <NUM> or 9a, which thus gives an estimated status of the animal <NUM>. For instance, in the case of a dog, the recognized movement or activity may be comprised in a number of predetermined statuses:.

For instance, if the estimated status is "barks", at step <NUM> the processor <NUM> may activate the microphone <NUM> for some time and record the sound captures by the microphone <NUM>.

At step <NUM>, the sound may be recognized by the neural network <NUM> or 9a, which thus gives a specified estimated status of the animal <NUM>. For instance, the specified estimated status may be "aggressive barking" "non-aggressive barking". More generally, the specified estimated status may reflect a psychological state of the animal corresponding to a type of barking or reflect the type of situation where the dog is (for instance, fight with another animal, fear or aggressivity due to an intrusion in the area where the dog is, etc.).

Similar steps may be performed with other animals than dogs, except that the predetermined status triggering step <NUM> will not be "barks" and the specified estimated status is not connected to barking but still may reflect a psychological state of the animal corresponding to the recorded sound or reflect the type of situation where the dog is based on the recorded sound.

In particular, steps <NUM>-<NUM> are also usable for a cat instead of a dog. In the case of a cat, at step <NUM>, the recognized movement or activity may be comprised in a number of predetermined statuses:.

In a second example, as illustrated in <FIG>, the first sensor may be the accelerometer <NUM> and the second sensor may be the satellite geolocation receptor <NUM>. The first parameter is thus acceleration and second parameter may be a number of satellites "seen" by the satellite geolocation receptor <NUM>.

At step <NUM>, the processor <NUM> detects movement of the animal <NUM> by the accelerometer <NUM>. The estimated status of the animal is then "moving".

At step <NUM>, the processor <NUM> determines the time T of movement of the animal <NUM> and whether it is wlaking or running, based on the measures given by the accelerometer <NUM>.

In case the animal <NUM> is walking and the walking time is longer than X mn, or in case the animal is running and the running time is larger than Y mn (Y being less than X), then the estimated status of the animal is set to "moving substantively" by the processor <NUM>. The processor <NUM> then activates the satellite geolocation receptor <NUM> at step <NUM> and detects the position of the animal at step <NUM>.

In a variant, at step <NUM>, the estimated status of the animal may be set to "moving substantively" by the processor <NUM> if : (the animal <NUM> is walking and the walking time is longer than X mn, or the animal is running and the running time is larger than Y mn) and (the animal is moving substantially according to a main direction). The condition "the animal is moving substantially according to a main direction" represents the fact that the animal is aiming somewhere and is not doing random movements. This condition may be detected by neural network <NUM> or 9a.

In a particular case, as illustrated on <FIG>, at step <NUM>, the processor <NUM> determines the number of satellites "seen" by the satellite geolocation receptor <NUM> (step <NUM>) and determines whether the animal is inside a home <NUM> (or any other building <NUM>) or outside the home <NUM> by said number of satellites: if this number is more than a predetermined threshold z (for instance <NUM> or <NUM>), the animal is out of home or more generally outside the building <NUM> (step <NUM>), otherwise it is at home or more generally inside the building <NUM> (step <NUM>). The specified estimated status is thus either "out of the building" or "inside the building". The estimated status and specified estimated status are transmitted to the user on his or her mobile device <NUM>.

In the method of <FIG>, at step <NUM>, the processor may activate the short range radio LAN interface <NUM>, for instance a WIFI interface, which is then used as second sensor. In that case, at step <NUM>, the processor <NUM> determines the second parameter which is a connectivity with at least one radio short range router 15a having a known position relative to said building <NUM> (for instance inside the building <NUM>). Such connectivity enables the processor to determine the specified estimated status which is chosen between "out of the building" and "inside the building".

In a third example, not part of the claimed subject matter, the first sensor may be the temperature sensor <NUM> and said first parameter is temperature.

This third example may be used for instance when said at least one animal includes a plurality of bees <NUM> (<FIG>) and said temperature sensor <NUM> is inside a hive <NUM> to which belongs said plurality of bees. Preferably the whole monitoring device <NUM> may be located inside the hive <NUM>.

In this third example, said second sensor is the microphone <NUM> and said second parameter is sound registered by the processor <NUM> from microphone <NUM>.

As illustrated at <FIG>, at step <NUM>, the processor <NUM> detects when temperature rises above a predetermined threshold (estimated status "high temperature"), indicating a possible stress of the bees <NUM> inside the hive <NUM>.

At step <NUM>, the processor <NUM> then activates the microphone <NUM> and records sound captured by the microphone <NUM>.

At step <NUM>, such sound is recognized by the system, in particular by the neural network <NUM> or 9a which is trained in this purpose, in particular to determine whether the hive <NUM> is being attacked by Asian hornets or other predator (specified estimated status "attack of hive").

In all cases where the second sensor is the microphone <NUM>, the analysis of the sound may be carried out either on a raw sound capture, or on a spectrogram thereof.

In a variant of the third example, the first sensor may be the accelerometer <NUM> and said first parameter is acceleration, while the second sensor is still the microphone <NUM> and said second parameter is sound registered by the processor <NUM> from microphone <NUM>.

Claim 1:
A method for monitoring at least one animal (<NUM>; <NUM>) with an autonomous monitoring device (<NUM>) being in close proximity to the animal (<NUM>; <NUM>), said monitoring device (<NUM>) having at least:
- a processor (<NUM>);
- a first sensor (<NUM>; <NUM>) communicating with the processor (<NUM>) and having a first electric power consumption;
- a second sensor (<NUM>; <NUM>; <NUM>) communicating with the processor (<NUM>) and having a second electric power consumption, said first electric power consumption being lower than the second electric power consumption,; and
- a battery (<NUM>) feeding at least said processor (<NUM>), first sensor (<NUM>; <NUM>) and second sensor (<NUM>; <NUM>; <NUM>); said method including:
- measuring a first parameter with the first sensor (<NUM>; <NUM>) while the second sensor (<NUM>; <NUM>; <NUM>) is deactivated,
- determining an estimated status of the animal based on the first parameter,
- if said estimated status corresponds to at least one predetermined status, activating the second sensor (<NUM>; <NUM>; <NUM>) and measuring a second parameter with said second sensor (<NUM>; <NUM>; <NUM>),
- determining a specified estimated status of the animal based on the second parameter,
wherein said monitoring device is worn by the animal (<NUM>), said first sensor is an accelerometer (<NUM>), said first parameter is acceleration, said animal (<NUM>) is hosted in a building (<NUM>) and has a possibility to move out of the building, said predetermined status is "moving substantively", said second sensor (<NUM>; <NUM>) is chosen in the group comprising:
- a satellite geolocation receptor (<NUM>), in which case the second parameter is a number of satellites from which the receptor receives signal; and
- a short range radio interface (<NUM>), in which case the second parameter is a connectivity with at least one radio short range router (15a) having a known position relative to said building (<NUM>),
and said specified estimated status is chosen between "out of the building" and "inside the building".