A device for monitoring the health of trees

Abstract

An apparatus (100) for monitoring the health of trees (TR) is described, the apparatus (100) including sensors (10A, 10B) configured to perform measurements of parameters indicative of the health of the trees (TR) and processing systems (110, 115) configured to process the measurements provided by the sensors (10A, 10B). The apparatus (100) is attached to the trees (TR) to be monitored and configured to perform measurements of the leaves (FO) of the trees (TR). The sensors (10A, 10B) include at least a multispectral sensor (10A) for performing optical measurements of the leaves (FO) of the trees (TR), the multispectral sensor (10A) being capable of performing optical measurements in the visible and near-infrared (NIR) spectrum. The apparatus (100) is configured to calculate a normalized difference vegetation index (NDVI) of the associated trees (TR) based on the optical measurements performed by the multispectral sensor (10A).

Description

[Technical Field]

[0001] The present invention relates generally to a device for monitoring the health of trees. [Background technology]

[0002] International (PCT) Publication No. WO 2022 / 049552 A1 in the name of the present applicant, the contents of which are incorporated herein by reference in their entirety, discloses a method and system for tracking, monitoring, and predicting the health of a plant heritage, such as an arboretum or forest, that includes a plurality of tree specimens. Each specimen in the plant heritage comprises a group of sensors configured to measure a plurality of parameters that are indicative of or may affect the health of the specimen. The measurement data generated by each sensor is collected locally and transmitted via a wireless network to a data collection center. The collected measurement data is used by the data collection center to characterize the health of each specimen and to build a predictive model of the health of each specimen. An assessment of the health of each specimen is performed based on the predictive model, and an alert is generated if the predictive model of the specimen's health indicates a hazard or another risk associated with a deterioration in the specimen's health.

[0003] European Patent Publication No. EP3531367A1 discloses a system and method for predicting the occurrence of tree disease. The system includes a memory unit that receives and stores first tree moisture information measured by a dedicated moisture sensor placed on the tree and second soil moisture information measured by another dedicated moisture sensor placed in the soil surrounding the tree. Additional sensors may be provided to measure the humidity and temperature of the environment in which the tree is located, or to measure the sugar content of the tree. A processing unit is further provided that predicts the occurrence of tree disease based on the first and second moisture information. However, this publication does not provide detailed descriptions of the sensor technologies used, and merely mentions measuring moisture content using heat pulses and sugar content using near-infrared spectroscopy.

[0004] European Patent Publication No. EP3421988A1 discloses an apparatus and method for continuously measuring the "stasis," i.e., stability over time, of one or more trees. The apparatus includes a three-axis motion sensor (such as a three-axis accelerometer), a data processing unit, a data transmitting unit, and a data receiving unit, all operatively connected to one another. Additionally, an anemometer may be operatively connected to the data receiving unit.

[0005] PCT Publication No. WO2019 / 069219A1 discloses a phytostatics analyzer for analyzing the phytostatic state of a tree, the device being designed to be attached directly to the tree and to measure and process tree vibrations. The phytostatics analyzer does not perform optical measurements.

[0006] Chinese Patent Publication No. CN103903400A discloses a device that includes an inclinometer (such as a 3-axis MEMS accelerometer) attached to the trunk of a tree, collects real-time acceleration data, processes the data to determine the tree's inclination, and compares it with a pre-set threshold to monitor and determine whether the tree is prone to falling and poses a potential danger to nearby people.

[0007] A similar principle is also described in "Tree tilt monitoring in rural and urban landscapes of Hong Kong using smart sensing technology" by Sawaid Abbas et al., published in "Trees, Forest and People," Volume 2, December 2020, 100030, Elsevier BV (https: / / doi.org / 10.1016 / j.tfp.2020.100030). In this case, accelerometers and vibration sensors are used to track the physical response of trees by measuring the rotation angle, tree displacement, and tree tilt angle with a tilt accuracy of 0.05°.

[0008] Yet another principle is disclosed in "IoT-Based Smart Tree Management Solution for Green Cities," Bilal Shabandri et al., "Internet of Things and Analytics for Agriculture," Volume 2, Studies in Big Data (SBD) 67, October 2019, pp. 181–199 (https: / / doi.org / 10.1007 / 978-981-15-0663-5_9). In this case, various sensors are implemented, including sound sensors, piezoelectric vibration sensors, light detectors, temperature and humidity sensors, air quality sensors, moisture sensors, and carbon dioxide sensors, resulting in a somewhat complex and costly sensor architecture that is costly and difficult to implement in practice, especially in portable / mobile solutions.

[0009] Focusing solely on the physical response of trees and measuring physical parameters such as tilt angle and tree movement may not provide sufficient indicators of tree health. While this technology may be able to reliably detect and predict the risk of tree toppling, it is difficult to accurately grasp the health of trees and build a reliable predictive model.

[0010] Therefore, as taught in the art, it would be preferable to rely more on other sensors to measure parameters other than purely physical parameters related to stability and / or tree movement, but this would come at the expense of complex sensor architectures that would be more difficult to implement and integrate into a reliable and cost-effective solution that would essentially be portable and autonomous from a power supply perspective.

[0011] The article entitled "New tree monitoring systems: from Industry 4.0 to Nature 4.0" by Riccardo Valentini et al., published in Annals of Silvicultural Research, Vol. 43, No. 2, November 30, 2019, pp. 84-89 (https: / / doi.org / 10.12899 / asr-1847), discloses a device according to the preamble of claim 1 (see also Italian Patent Publication No. IT102019000013362A1, entitled "DISPOSITIVO E SISTEMA PER IL RILIEVO DELLO STATO DI SALUTE DI UNA O PIU'PIANTE"). This device (known as TreeTalker or by the acronym "TT") includes a multispectral sensor for optical measurements of tree leaves. The multispectral sensor is designed to perform optical measurements in 12 spectral bands centered at approximately 450 nm, 500 nm, 550 nm, 570 nm, 600 nm, 610 nm, 650 nm, 680 nm, 730 nm, 760 nm, 810 nm, and 860 nm, enabling, for example, remote calculation of the Normalized Difference Vegetation Index (NDVI). The aforementioned TT device is not configured to perform on-board calculation of the Normalized Difference Vegetation Index (NDVI), but is essentially configured to communicate optical measurements (and other measurements) in semi-real time via a wireless communication unit configured to operate according to the LoRaWAN communication protocol. In practice, measurement data is transmitted to a nearby node (or "TT node"), which can accommodate a cluster of multiple TT devices, with data transmission typically set to an hourly frequency. The TT node is connected to the Internet via a GPRS network and transmits the data to a computer server, which collects it. Such data can be retrieved from a computer server and processed to extract information that indicates the health of the trees on which the TT devices are installed.

[0012] The aforementioned TT device is also outlined in a presentation written by Riccardo Valentini on February 27, 2019, entitled "The TreeTalker network: Let's trees talk about climate" (https: / / www.slideshare.net / lifeurbangreen / the-treetalker-network-lets-trees-talk-about-climate).

[0013] The aforementioned TT device further includes sensors to measure sap flow, trunk humidity, trunk radial growth, trunk axial movement, and air temperature and humidity. Sap flow density is specifically obtained by monitoring the temperature of two 20 mm long probes inserted into the trunk wood at a distance of 10 cm along the longitudinal axis of the trunk. This is an invasive measurement that is undesirable in practice, as it could be detrimental to tree health.

[0014] Another limitation of the aforementioned TT device is the location of the multispectral sensor mounted on top of the device's main housing, which is directly attached to the tree trunk by a belt fastened to the trunk. This significantly limits the positioning of the TT device and the ability of the associated multispectral sensor to properly detect light passing through the tree canopy, essentially affecting the reliability of the optical measurements. For this reason, the solar panel used to charge the device's battery must also be installed in a separate housing attached and electrically connected to the device's main housing.

[0015] European Patent Publication No. EP3473081A1 generally relates to an information processing device and method, which in one embodiment may be applied for the purpose of performing mobile observation and fixed-point observation. Specifically, a fixed-point measurement device is fixed at a position where it can sense a measurement target, such as a plant in a field. This fixed-point measurement device may include, among other things, a sensing device for measuring a normalized difference vegetation index (NDVI) value. However, this patent publication does not specifically mention any application to tree health monitoring.

[0016] PCT Publication No. WO 2016 / 181743 A1 generally relates to a plant growth index measurement device and method adapted to perform measurements on plants having multiple leaves, including optical measurements of Normalized Difference Vegetation Index (NDVI) values. However, the patent application is silent about the application of the related plant growth index measurement device and method to tree health monitoring in particular. In any case, Figure 1 of PCT Publication No. WO 2016 / 181743 A1 shows that the device is not intended to be attached directly to the observed plant, but rather is positioned at a distance from the observed plant to derive measurements based on the relative direction of sunlight.

[0017] JP 2022-087038 A describes a vegetation condition detection system and method that can detect the condition of vegetation beneath a safety net or disaster prevention net using a remote optical observation device, such as an unmanned aerial vehicle (UAV) equipped with a camera, positioned above the safety net or disaster prevention net. The essence of this solution is that it is mobile, can perform optical measurements over a wide area, and is not affected by the presence of the safety net or disaster prevention net, which may block at least part of the field of view. Therefore, it is clear that this solution is not intended or adapted to be attached directly to trees for the purpose of monitoring the health of the trees.

[0018] Therefore, there remains a need for improved solutions. Summary of the Invention

[0019] A general object of the present invention is to provide a tree health monitoring device that overcomes the problems and limitations of known solutions.

[0020] More specifically, it is an object of the present invention to provide a device that offers a good compromise between the representativeness of the measurements and the required robustness and cost-effectiveness of the implementation.

[0021] It is a further object of the present invention to provide an apparatus that can reliably provide a representative measurement of tree health.

[0022] It is yet another object of the present invention to provide a device that can be mounted directly on the trees to be monitored, that is a portable and easily deployable solution, and that can be successfully and reliably implemented.

[0023] These objects are achieved by the solutions defined in the claims.

[0024] According to the present invention, there is provided an apparatus for monitoring the health of trees, characterized in that it comprises a sensor configured to perform measurements of parameters indicative of the health of the trees, and a processing system configured to process measurements provided by the sensor. The apparatus is attached to the trees to be monitored and is configured to perform measurements of the tree leaves. The sensor includes at least a multispectral sensor for performing optical measurements of the tree leaves, the multispectral sensor being capable of optical measurements in the visible and near-infrared (NIR) spectrum. According to the present invention, the apparatus is configured to calculate a Normalized Difference Vegetation Index (NDVI) of the associated trees based on the optical measurements by the multispectral sensor.

[0025] In one embodiment, the multispectral sensor includes a first detector capable of performing a first optical measurement in the blue and / or red spectrum and a second detector capable of performing a second optical measurement in the near-infrared spectrum. In this case, the normalized difference vegetation index (NDVI) is preferably calculated taking into account a recalibration factor calculated based on optical measurements performed by the first and second detectors in substantially the same spectral band. In another embodiment, the multispectral sensor includes a single detector capable of performing both a first optical measurement in the blue and / or red spectrum and a second optical measurement in the near-infrared (NIR) spectrum. Preferably, the multispectral sensor is configured to perform a first optical measurement in the blue spectrum, particularly a spectral band centered around 450 nm, and the device is configured to calculate the normalized difference vegetation index (NDVI) based on the first optical measurement performed in the blue spectrum and the second optical measurement performed in the near-infrared (NIR) spectrum.

[0026] According to a preferred embodiment, the electronic components of the device, including the sensor and processing system, are housed in a casing that is attached to the tree to be monitored via an orientable mount supporting the casing, where the device is configured such that the casing can be oriented relative to the tree by the orientable mount so as to direct the multispectral sensor toward a selected portion of the tree's foliage. In this context, the casing preferably includes a casing portion that is substantially transparent to the measurement spectrum of the multispectral sensor. Advantageously, the device further comprises an adjustable mounting mechanism secured to a base of the orientable mount for mounting to the trunk or branches of the tree. The adjustable mounting mechanism may be extendable, in particular to prevent strangulation of the tree over time.

[0027] According to another aspect of the invention, the sensors further include a stability sensor that measures the stability of the tree, and the device is further configured to calculate an index of tree stability based on the measurements made by the stability sensor. The stability sensor may include, among other things, an accelerometer or an inclinometer that measures the degree of lean of the tree and / or monitors changes in the degree of lean of the tree over time.

[0028] In one embodiment, the device may further comprise a trigger sensor, such as an acceleration sensor, for detecting sudden tree movements, which may be used to activate the system, especially in the event of a sudden tree movement.

[0029] Preferably, the device further comprises a battery for powering the device. Such a battery may be rechargeable, in particular by an energy harvesting device such as a photovoltaic cell. Preferably, the battery and energy harvesting device, if any, are housed in the same casing as other electronic components of the device, including the sensor and processing system.

[0030] According to a particularly preferred embodiment, the device further comprises a communication unit configured to transmit data indicative of the health of the tree to a remote station, the data transmitted by the communication unit comprising or at least based on a Normalized Difference Vegetation Index (NDVI) calculated by the device.

[0031] In one embodiment, the device is configured to supply power to the sensors only when measurements are being performed, and to this end preferably further comprises a first switch for selectively supplying or cutting off power to the sensors individually or collectively. Even more preferably, the device is configured to supply power to the sensors and / or communication unit only when measurements are being performed or when data is being transmitted. In such a case, the device preferably further comprises a first switch for selectively supplying or cutting off power to the sensors individually or collectively, and a second switch for selectively supplying or cutting off power to the communication unit.

[0032] Said communication unit may advantageously be a wireless communication unit configured to wirelessly transmit data to a remote station, such as a wireless communication unit configured to operate according to the LoRaWAN or NB-IoT communication protocol.

[0033] Finally, according to a further advantageous embodiment, the device may comprise a data logger for at least temporarily storing the data transmitted via the communication unit, optionally also storing the data on a portable storage medium such as an SD card.

[0034] Further advantageous embodiments of the invention are described below. [Brief explanation of the drawings]

[0035] Other characteristics and advantages of the present invention will become more apparent on reading the following detailed description of embodiments of the invention given by way of non-limiting example only and illustrated by the accompanying drawings, in which: [Figure 1] FIG. 1 is a schematic overview of a system for tracking and monitoring the health of a population of trees, each equipped with sensors and data collection units such as the device of the present invention. [Figure 2] FIG. 2 is a schematic diagram of a tree fitted with a device according to one embodiment of the present invention. [Figure 3] FIG. 3 is a photograph of a prototype of an apparatus according to an embodiment of the present invention. [Figure 4] FIG. 4 is a schematic functional diagram of the main electronic components of an apparatus according to a preferred embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0036] The present invention will be described with particular reference to various exemplary embodiments as shown in Figures 1-4. The scope of the invention is defined by the appended claims and should be understood to encompass all combinations and subcombinations of the features of the invention disclosed herein.

[0037] FIG. 1 is an overall schematic diagram of a system for tracking and monitoring the health of a population of trees PT, including a plurality of tree specimens Ai (A.1, A.2, A.3, etc.), each equipped with a sensor and data collection unit 10.i (10.1, 10.2, 10.3, etc.). Such a system is generally described in International (PCT) Publication No. WO 2022 / 049552 A1, previously mentioned in the preamble herein. The tree specimens Ai are geographically distributed in a particular area and may be trees planted in urban and / or rural areas, such as cities, parks, forests, orchards, etc. Each sensor and data collection unit 10.i generates measurement data DATA indicative of the health of each tree specimen Ai. A.i This data is configured to allow the collection of A.i The data collected from the multiple data collection points can be suitably transmitted to the data collection server 1000, for example, via a suitable wireless communication network. PT The set of data, called * The data is processed by the data processing unit 1000, and the health status of the entire population of trees PT can be tracked both collectively and individually. The data collection server 1000 may be a cloud server accessible via the Internet, and the remote workstation 1000 may be a cloud server accessible via the Internet. * is essentially any suitable workstation 1000, including a computer station or smartphone or tablet, that can access the data collected by the data collection server 1000. * It could be.

[0038] FIG. 2 is a schematic diagram of a tree TR, representing one of the associated tree specimens Ai shown in FIG. 1, including an apparatus, generally designated 100, according to one possible embodiment of the present invention, which may function as a suitable sensor and data collection unit 10.i in the context of the system shown in FIG. 1. The apparatus 100 is preferably specifically designed to monitor the health of the tree TR by performing a combination of optical measurements of the leaves F0 of the tree TR, along with measurements of the tree TR's stability. As described below, the apparatus 100 includes dedicated sensors for performing such measurements and an associated processing system configured to process the measurements. Preferably, data collected by the apparatus 100 is also wirelessly transmitted via a suitable wireless communication network to a remote station (such as the data collection server 1000 depicted in FIG. 1). In the illustrated example, the apparatus 100 is preferably attached to the trunk TK of the tree TR by a suitable attachment mechanism 155. More preferably, device 100 is coupled to a mounting mechanism 155 via an orientable mount 150 such that device 100 can be appropriately oriented to observe a desired portion of a leaf FO, i.e., by orienting a field of view FV of device 100 toward a desired portion of a leaf FO, as shown schematically. The electronic components of device 100, including the aforementioned sensors and associated processing system, are preferably housed within a casing 130 that is attached to the orientable mount 150.

[0039] In practice, the device 100 is preferably mounted on the tree TR at a high position along the trunk TK out of reach of bystanders, preferably at a height of around 2.5 to 3 meters.

[0040] The orientable mount 150 may be any suitable support mechanism that can be adjusted to change the orientation of the casing 130 and locked in place so that the casing is stably secured to the associated trunk TK. The orientable mount 150 may be comprised of an articulated link having one or more degrees of freedom, including, among other things, an adjustable arm attached to a pivot or ball joint so that it can be locked into one of multiple possible orientations. The adjustable mounting mechanism 155 is preferably stretchable to prevent pinching of the tree TR over time, and may, among other things, include a stretchable fastening belt (and associated tensioning system) that can be wrapped around the trunk TR (or branches) of the tree TR.

[0041] Figure 3 is a photographic representation of a prototype of device 100 according to one embodiment of the present invention, shown here attached to a sawed surface of trunk TK. Visible in Figure 3 are attachment mechanism 155, which in the illustrated example comprises an expandable belt wrapped around trunk TK, orientable mount 150 supported by its base on attachment mechanism 155, and casing 130 housing the electronic components of device 100, including electronic module 110 carrying sensors 10A, 10B.

[0042] 3, the casing 130 is preferably light-colored to reflect as much incident light as possible and prevent overheating problems. In this regard, the underside of the casing 130 can be designed to increase thermal conductivity and act as a heat sink to dissipate heat generated by the electronic components of the device 100.

[0043] As will be described below, electronic module 110 includes at least a multispectral sensor, designated 10A, designed to perform optical measurements of leaves FO of tree TR, and preferably a stability sensor, designated 10B, designed to perform measurements of tree TR stability. In that regard, casing 130 includes a casing portion (here, cover portion 130A) that is substantially transparent to the measurement spectrum of multispectral sensor 10A. While FIG. 3 illustrates cover portion 130A as being substantially transparent, it will be understood that casing 130 may include one or more dedicated windows positioned along the field of view FV of multispectral sensor 10A.

[0044] In the illustrated example, electronic module 110 further comprises a photovoltaic cell PV that functions as an energy harvester to provide power for charging a battery (not shown) of device 100. In this regard, photovoltaic cell PV may be located within casing 130 protected by cover portion 130A, as shown, or may be located on an outer portion of casing 130.

[0045] 4 is a schematic functional diagram of the main electronic components of a device according to a preferred embodiment of the invention. In the example shown, all the main electronic components are advantageously provided in a common electronic module 110: · a microcontroller or microprocessor 115 that handles most of the data processing; a multispectral sensor 10A (here including first and second detection devices 10A-1, 10A-2); ·Stability sensor 10B; ·Trigger sensor 10C; a first switch SW1 controlling the power supply to the sensors 10A, 10B; · wireless communication unit 120; a second switch SW2 that controls the power supply to the wireless communication unit 120; Data logger 125 Rechargeable battery BAT; a charging circuit CHR that controls the charging of the battery BAT; and ·Solar PV

[0046] Mounting all relevant electronic components of the device 100 on the same PCB module 110 provides benefits in terms of reliability and manufacturing cost-effectiveness compared to known solutions that rely on the use of multiple interconnected devices, for example.

[0047] If necessary, additional sensors may be provided, including sensors capable of measuring representative parameters of the environment in which the tree TR is planted, such as environmental temperature and humidity. Referring to the disclosure of International (PCT) Publication No. WO 2022 / 049552 A1, the contents of which are incorporated herein by reference, such additional sensors may be placed on or next to the tree TR at other desired locations, such as in the soil or next to the roots of the tree TR, to measure soil humidity. In such cases, the additional sensors must be located away from the casing 130 housing the main electronic components of the device 100, and operative coupling with the electronic module 110 may be ensured by a suitable wired connection to each remote sensor or via a wireless local interconnection between the electronic module 110 and each remote sensor. Such additional sensors may, in fact, be provided at any desired location, including, for example, on the orientable mount 150 or its base.

[0048] Additional sensors may also be provided to measure operating parameters of the device 100 itself, such as temperature and humidity, which may affect the operation of the device 100.

[0049] The aforementioned wireless communication unit 120 is preferably a wireless communication unit operating according to the LoRaWAN (Long Range Wide Area Network) communication protocol, which typically allows wireless communication over a range of 5-10 km with relatively low power consumption (assuming, in practice, that there is adequate corresponding network coverage). Suitable LoRa modules are commercially available from Semtech Corporation (https: / / www.semtech.com / ).

[0050] Other low-power communication protocols may be considered, including the Narrowband Internet of Things (NB-IoT) communication protocol. LoRaWAN and NB-IoT protocols should be considered, as these protocols provide for the establishment of low-power wide-area networks that allow wireless communication of data over relatively long distances (approximately 5-15 km, depending on the technology). This low-power requirement is key to ensuring the feasibility of a solution that must be inherently portable and easily deployable over a potentially wide area.

[0051] It is also contemplated that data may be transmitted wirelessly via any suitable cellular network (such as a GSM or GPRS network) or via a suitable satellite uplink.

[0052] Switches SW1, SW2 may be simple MOS-FET switches designed to selectively supply and cut off power to associated sensors 10A, 10B (referred to collectively herein) and communication unit 120, respectively. More specifically, sensors 10A, 10B and communication unit 120 are advantageously powered only when measurements are being performed and when data is being transmitted, respectively, which is important to ensure that device 100 can operate satisfactorily on the power provided by battery BAT. In this regard, photovoltaic cells PV help to improve the power autonomy of device 100 over the long periods, i.e., months or years, required to ensure adequate monitoring of the health of trees TR.

[0053] In other words, device 100 is preferably configured to enter a low-power sleep mode when measurements are not needed to conserve power, and to be woken up periodically to perform desired measurements. The frequency with which measurements are performed may vary depending on practical considerations and requirements. By way of example, device 100 may be woken up, e.g., every 10 minutes, to perform and / or transmit relevant measurements, although higher or lower operating frequencies are contemplated. Additionally, device 100 may operate less frequently if the battery state of charge becomes low.

[0054] As the data may only be transmitted periodically, a data logger 125 is provided to temporarily store the data (raw measurement data from the sensors 10A, 10B or processed data processed by the microcontroller / microprocessor 115) until it is transmitted via the communication unit 120. This data logger 125 also ensures that the data is not lost in the event of a power outage. In that regard, it is also conceivable to store the data on a suitable portable storage medium such as an SD card.

[0055] The primary purpose of the trigger sensor 10C is to detect sudden movement of the tree TR, which may be triggered by a significant event, such as a sudden collapse of the tree TR or other significant event affecting the structural integrity of the tree TR. The trigger sensor 10C comprises a motion sensor, such as an ultra-low power, high-performance 3-axis linear acceleration sensor, such as that sold by ST Microelectronics (https: / / www.st.com / ) under product number LIS2DH12. The trigger sensor 10C is primarily used to activate the system in the event of sudden movement of the tree TR. Additionally, the device 100 may be equipped with an alarm device that issues an audible alarm when the trigger sensor 10C detects sudden movement of the tree TR.

[0056] If desired, a suitable initialization switch or trigger (not shown), such as a jumper, sealed switch, or the like, may be provided to facilitate initialization of operation of the device 100 once the device 100 is mounted on the tree TR and properly oriented so that the field of view FV of the multispectral sensor 10A is directed toward the appropriate portion of the leaf FO. Once properly installed and oriented, operation of the device 100 can be initialized by actuating the associated initialization switch or trigger.

[0057] In accordance with the present invention, multispectral sensor 10A is designed to perform optical measurements of leaves FO of a tree TR, as shown schematically in Figure 2, and apparatus 100 is configured to calculate a Normalized Difference Vegetation Index (abbreviated "NDVI") for the tree TR based on such optical measurements. Specifically, multispectral sensor 10A is capable of optical measurements in the visible and near-infrared (NIR) spectrum.

[0058] The rationale for NDVI is that living green plants (including trees) absorb sunlight in the photosynthetically active radiation (PAR) spectral region (i.e., wavelengths between approximately 400 and 700 nm) and use it as an energy source in the process of photosynthesis. Some of this energy is then re-emitted in the near-infrared (NIR) spectral region (i.e., wavelengths between 700 and 1,100 nm). In other words, living, healthy green plants appear relatively dark in the PAR spectral region and relatively bright in the NIR spectral region. In fact, chlorophyll, the most abundant green pigment in green plants, primarily absorbs in the blue and red spectrum, i.e., chlorophyll b around 450 nm and chlorophyll a around 650 nm.

[0059] From an analytical standpoint, NDVI is usually calculated as a difference measurement between reflectance measured in the red and near-infrared (NIR) spectra according to the following ratio: NDVI=(IR-R) / (IR+R) where IR is the reflectance measured in the near-infrared spectrum and R is the reflectance measured in the red spectrum, which corresponds to photosynthetic activity primarily associated with chlorophyll a. However, it is also possible to measure reflectance in the blue spectrum, which corresponds to photosynthetic activity primarily associated with chlorophyll b, and calculate the corresponding NDVI in a similar manner. In this case, the same ratio is calculated, but the main difference is in R, which represents the reflectance measured in the blue spectrum.

[0060] In one embodiment, as shown schematically in Figure 4, a multispectral sensor 10A includes a first detector 10A-1 that is sensitive to the visible spectrum and performs a first optical measurement in the red (or blue) spectrum, and a second detector 10A-2 that is sensitive to the near-infrared (NIR) spectrum and performs a second optical measurement in the NIR spectrum. The prototype shown in Figure 3 was conceived based on this basis and uses, in particular, multispectral sensors available from ams-OSRAM AG (https: / / ams-osram.com / ) under product numbers AS7262 and AS7263. The AS7262 component is a multispectral sensor sensitive to six measurement channels (or spectral bands) in the visible spectrum, namely, 450 nm, 500 nm, 550 nm, 570 nm, 600 nm, and 650 nm. The AS7263 component is a multispectral sensor sensitive to the infrared and near-infrared (NIR) spectrum in six measurement channels (or spectral bands): 610nm, 680nm, 730nm, 760nm, 810nm, and 860nm.

[0061] Depending on preference, the NDVI is calculated in this case for the spectral band centered at 450 nm, i.e. the blue spectrum (using the aforementioned AS7262 component) and for the spectral band centered at 860 nm (using the aforementioned AS7263 component), tests demonstrating that this particular choice gives the best results.

[0062] In this case, two different multispectral sensors are used, so both sensors were rebalanced, assuming that optical measurements using both sensors in the same spectral band would yield the same values. In this example, it is assumed that the spectral band centered at 600 nm (using the AS7262 component) and the spectral band centered at 610 nm (using the AS7263 component) should yield substantially the same values.

[0063] In other words, considering the above example, the NDVI is preferably calculated according to the following ratio: NDVI=(R860-R450*C) / (R860+R450*C) where R860 is the reflectance measured at approximately 860 nm (using the AS7263 component), R450 is the reflectance measured at approximately 450 nm (using the AS7262 component), and C is the recalibration factor calculated as follows: C=R610 / R600 where R610 is the reflectance measured at approximately 610 nm (using the AS7263 component) and R600 is the reflectance measured at approximately 600 nm (using the AS7262 component).

[0064] The above example illustrates a possible embodiment of the present invention, assuming the use of two different multispectral components readily available on the market. It is further understood that this example takes into account the relevant specifications of each component and the inherent constraints that arise therefrom. Other sensor combinations are also contemplated, but may require appropriate modifications to the calculation methodology.

[0065] In other embodiments, it is entirely conceivable to use a single multispectral sensor that is sensitive in both relevant spectral bands, i.e., in the blue and / or red spectrum (e.g., around 450 nm and / or 650 nm, respectively) on the one hand, and in the near-infrared (NIR) spectrum (e.g., a selected spectral band from about 700 nm to 1,100 nm) on the other hand. In such cases, the use of a single detection device has the advantage that no recalibration is required.

[0066] A peculiarity of the aforementioned approach is that since the multispectral sensor 10A is typically installed facing upwards towards the leaves FO of the tree TR, portions of the blue sky may be substantially present within the field of view FV of the sensor 10A, depending on the associated density of the leaves FO, which may vary throughout the year. In other words, assuming trees with non-permanent leaves that change color in the fall and disappear in the winter, the reflectance of the relevant spectral bands will show large variations throughout the year, with an increase in NDVI in spring and summer when the leaves FO are most dense and green, and a decrease in NDVI in the fall and winter when the leaves FO become less dense or absent and change color.

[0067] According to a preferred embodiment, as shown schematically in FIG. 4, the sensor further includes a stability sensor 10B for measuring the stability of the tree TR, and the device 100 is further configured to calculate an index of the tree TR's stability based on the measurements performed by the stability sensor 10B. Such a stability sensor 10B may include, among other things, an accelerometer or inclinometer for measuring the degree of tilt of the tree TR and / or for monitoring changes in the degree of tilt of the tree TR over time. By way of example, the prototype shown in FIG. 3 was designed based on a three-axis high-precision inclinometer available from muRata (https: / / www.murata.com / ) under product number SCL3300. Such an inclinometer is capable of measuring tilt angles with an output resolution of 0.0055° / LSB.

[0068] In this embodiment, the stability sensor 10B is configured to measure the movement of the device 100 (assuming it is fixed to the tree TR and follows its movement). After the device 100 is installed in its final position on the tree, it is calibrated to provide a baseline for subsequent comparison. As the tree TR moves, and thus the device 100 and, therefore, the stability sensor 10B, the corresponding changes are detected by the inclinometer 10B, which allows the change in tilt of the tree TR over time to be calculated. In effect, by appropriately processing the information provided by the inclinometer 10B, the degree of tilt, its changes, and even the direction of movement of the tree TR can be determined. Because the only forces acting on the inclinometer 10B are those generated by gravity (assuming the tree is stable during measurements), rotational movement about the associated vertical axis may not result in a change in the associated measurement component of the inclinometer 10B. Therefore, it is difficult to determine the direction of tree movement with a high degree of accuracy; in practice, only a general indication of such direction may be identified. However, such an overall indicator is sufficient to determine and assess the risk of tree TRs collapsing onto specific zones such as nearby roads and sidewalks.

[0069] Various modifications and / or improvements can be made to the above-described embodiments without departing from the scope of the present invention, which is defined by the appended claims. [Explanation of symbols]

[0070] 100 Tree TR health monitoring device 10A Multispectral Sensor 10A-1 Detecting devices sensitive to the visible spectrum (especially the blue and / or red spectrum) 10A-2 Detectors sensitive to the near-infrared (NIR) spectrum 10B Stability sensors (accelerometers, inclinometers, etc.) 10C Trigger sensor (accelerometer, etc.) 110 Electronic Module 115 Microcontrollers / Microprocessors 120 Transceiver unit (LoRaWAN unit, etc.) 125 Data Logger (DL) 130 Casing 130A Transparent Cover 150 Orientable Mount 155 Adjustable attachment mechanism BAT Rechargeable battery CHR Battery charging circuit PV solar cell SW1 (first) switch (power supply to sensors 10A and 10B) SW2 (second) switch (power supply to transceiver unit 120) TR trees TK tree trunk FO Tree TR Leaves FV Field of view of multispectral sensor 10A PT The population of monitored tree specimen Ai Ai Individual tree specimens 10.i. Sensors and data collection units (e.g., devices 100) installed on each tree specimen Ai 1000 Remote server for data collection 1000 * Remote workstation for data processing

Claims

1. An apparatus (100) for monitoring the health of a tree (TR), comprising sensors (10A, 10B) configured to perform measurements of parameters indicative of the health of the tree (TR), and a processing system (110, 115) configured to process the measurements provided by the sensors (10A, 10B), The device (100) is attached to a tree (TR) to be monitored and is configured to perform measurements of leaves (FO) of the tree (TR); The sensors (10A, 10B) include at least a multispectral sensor (10A) for performing optical measurements of leaves (FO) of a tree (TR), the multispectral sensor (10A) being capable of performing optical measurements in the visible spectrum and near-infrared (NIR) spectrum; The device (100) is configured to calculate a normalized difference vegetation index (NDVI) of an associated tree (TR) based on optical measurements performed by a multispectral sensor (10A).

2. 2. The apparatus (100) of claim 1, wherein the multispectral sensor (10A) includes a first detection device (10A-1) capable of performing a first optical measurement in the blue spectrum and / or the red spectrum, and a second detection device (10A-2) capable of performing a second optical measurement in the near-infrared (NIR) spectrum.

3. 3. The apparatus (100) of claim 2, wherein the Normalized Difference Vegetation Index (NDVI) is calculated taking into account a recalibration factor calculated based on optical measurements performed by the first and second sensing devices (10A-1, 10A-2) in substantially the same spectral band.

4. 10. The apparatus (100) of claim 1, wherein the multispectral sensor (10A) includes a single detection device capable of performing both a first optical measurement in the blue and / or red spectrum and a second optical measurement in the near-infrared (NIR) spectrum.

5. a multispectral sensor (10A) configured to perform a first optical measurement in the blue spectrum, in particular in a spectral band centered at about 450 nm; 5. The apparatus of claim 2, wherein the apparatus is configured to calculate a Normalized Difference Vegetation Index (NDVI) based on a first optical measurement measured in the blue spectrum and a second optical measurement measured in the near infrared (NIR) spectrum.

6. The electronic components of the device (100), including the sensors (10A, 10B) and the processing system (110, 115), are housed within a casing (130), which is attached to the tree (TR) to be monitored via an orientable mount (150) that supports the casing (130); The device (100) is configured such that the casing (130) is orientable relative to the tree (TR) by an orientable mount (150) so that the multispectral sensor (10A) is directed toward a selected portion of the leaves (FO) of the tree (TR).

7. The apparatus (100) of claim 6, wherein the casing (130) includes a casing portion (130A) that is substantially transparent to a measurement spectrum of the multispectral sensor (10A).

8. The device (100) of claim 6 or 7, further comprising an adjustable mounting mechanism (155) fixed to the base of the orientable mount (150) for mounting to the trunk (TK) or branches of a tree (TR).

9. 9. The device (100) of claim 8, wherein the adjustable attachment mechanism (155) is extendable to prevent strangulation of the tree (TR) over time.

10. the sensors (10A, 10B) further comprise a stability sensor (10B) for performing measurements of tree (TR) stability, The device (100) of any one of claims 1 to 9, further configured to calculate an index of tree (TR) stability based on measurements by the stability sensor (10B).

11. The device (100) of claim 10, wherein the stability sensor (10B) includes an accelerometer or an inclinometer and measures the degree of inclination of the tree (TR) and / or monitors changes in the degree of inclination of the tree (TR) over time.

12. The device (100) according to any one of claims 1 to 11, further comprising a trigger sensor (10C) such as an acceleration sensor for detecting sudden movements of the tree (TR).

13. The device (100) of any one of claims 1 to 12, further comprising a battery (BAT) for powering the device (100).

14. 14. The device (100) according to claim 13, characterized in that the battery (BAT) is rechargeable by an energy harvesting device such as a photovoltaic cell (PV).

15. 15. The device (100) according to claim 13 or 14, wherein the battery (BAT) and, if present, the energy harvesting device are housed in the same casing (130) together with other electronic components of the device (100), including the sensors (10A, 10B) and the processing system (110, 115).

16. a communication unit (120) configured to transmit data indicative of the health status of the tree (TR) to a remote station (1000, 1000*); 16. The apparatus (100) of claim 1, wherein the data transmitted by the communication unit (120) includes or is based on at least a Normalized Difference Vegetation Index (NDVI) calculated by the apparatus (100).

17. 17. The device (100) of any one of claims 1 to 16, wherein the device (100) is configured to supply power to the sensors (10A, 10B) only when a measurement is to be performed.

18. 18. The apparatus (100) of claim 17, further comprising a first switch (SW1) for selectively supplying or disconnecting power to the sensors (10A, 10B) individually or collectively.

19. The device (100) according to claim 16, characterized in that the device (100) is configured to supply power to the sensors (10A, 10B) and / or the communication unit (120) only when measurements are performed and / or when data is transmitted.

20. 20. The device (100) of claim 19, further comprising a first switch (SW1) for selectively supplying or disconnecting power to the sensors (10A, 10B) individually or collectively, and a second switch (SW2) for selectively supplying or disconnecting power to the communication unit (120).

21. 21. The apparatus (100) of claim 16, 19 or 20, wherein the communication unit (120) is a wireless communication unit (120) configured to wirelessly transmit the data to the remote station (1000, 1000*).

22. The apparatus (100) of claim 21, wherein the wireless communication unit (120) is configured to operate according to a LoRaWAN or NB-IoT communication protocol.

23. 23. The apparatus (100) of any one of claims 16, 19, 20, 21 and 22, further comprising a data logger (125) for at least temporarily storing data until the data is transmitted via the communication unit (120).

24. 24. The device (100) according to claim 23, characterized in that the data is stored on a portable storage medium such as an SD card.

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