A method for monitoring an environment

Abstract

A method for monitoring an environment (e.g. a office, house), comprising determining that the environment (100, figure 1) is in an initial (safe) state. Identifying, via one or more wireless network protocols (Wi-Fi®, BLE), first one or more (user owned) devices (101, 103), located within the environment whilst the environment is in the initial state. Categorising each of the devices into a first set of categories of devices (e.g. user owned / friendly devices), and storing the identity and associated category in a data store. Identifying, via the wireless network protocols, a second one or more (unknown) devices (205, figure 2), 305, located within the environment. Searching the data store, and determining whether the identity of the second devices is stored. If the identity of the second devices is not stored, or if at least one of the identities of the second devices is stored in the data store with a category (unsafe) which is not in the first set of categories, then determining that the environment is in a subsequent (alert or unsafe) state different to the initial state. In response to receiving a trigger (e.g. detected motion (i.e. using Wi-Fi sensing) due to an intruder 307 moving), performing one or more actions (e.g. initiate an alarm 309) if it is determined that the subsequent state is different to the initial state. If the environment does not comprise a user-owned device, the environment may be in an unsafe state, or an alert state.

Description

FIELD OF INVENTION The present invention relates to a method for monitoring an environment that determines a state of an environment based on one or more devices determined within the environment. BACKGROUND Consumers often have numerous electrical devices, some of which are carried around with them. Most often, a device Global Positioning System (GPS) is used to retrieve location information. However, GPS is largely limited to outdoor use. Therefore, at other instances, the consumer relies upon a cellular or Wi-Fi network connection to obtain this information. Information about one or more wireless devices can be determined using Wi-Fi and Bluetooth to determine a MAC address to identify the devices on a network. However, Wi-Fi and Bluetooth have a high-power consumption which impacts consumer experience for at least the reason that as it is not possible to identify devices on a network if a device is in power saving mode and Wi-Fi connection has been disabled. Bluetooth Low Energy (BLE) been designed to be energy efficient, such that its use reduces power consumption compared to the use of Bluetooth. BLE has a connected and a non-connected mode. In the non-connected mode, BLE devices announce their presence by broadcasting an advertisement packed on one or more advertising channels, and repeats this pseudo-periodically at a fixed interval, plus a random delay to avoid collisions. On the receiving end, a scanner, such as a smartphone, scans the medium for advertisements by listening to a specific channel during a scan window. The scanner iterates over all advertising channels by switching channels after a period called scan interval. A device initiates a connection by responding to an advertisement. The payload of BLE advertisements consists of a list of optional fields called Advertising Data (AD). Devices include AD to define, e.g., their device name, address, the list of offered services (such as sound or heart rate sensor), or data related to its specific manufacturer. Each AD is identified by its universally unique identifier (UUID), defined in the BLE standard. Therefore, known methods use BLE to connect a device with multiple other devices, where it is possible to identify each of the connected devices using the advertising data (e.g. identify the device as a speaker, or a smartphone). Valentin Poirot, Oliver Harms, Hendrie Martens, and Olaf Landsiedel. 2022. BlueSeer: Al-driven environment detection via BLE scans. In Proceedings of the 59th ACM / IEEE Design Automation Conference (DAC '22). Association for Computing Machinery, New York, NY, USA, 871-876. https: / / doi.org / 10.1145 / 3489517.3530519 provides a method used to classify environments using an environment-detection system that solely relies on received BLE packets and an embedded neural network. However, the method disclosed in the publication is for identification of a number of devices in the surrounding area of a device, where the information gathered about the devices enables the environment to be categorised (e.g. home, office, shopping, transport, nature, street, and restaurant). Whilst it is disclosed that the environment is classified into types, it cannot provide the status of an environment at different times, or react as an environment changes. SUMMARY Against this background, the present disclosure provides a method and system for monitoring an environment. The method may be performed at a device, wherein the device may be a router (consumer-premises equipment - CPE), or the method may be carried out by a system comprising a device (e.g. a router). The method firstly may determine that an environment is in an initial state. The environment may be a predetermined area of space, which comprises one or more devices. The environment may comprise a router wherein the router provides internet communication services to one or more clients over a wired or wireless communication protocol, such as ethernet or Wi-Fi. The router is connected to the internet either using a cable connection (e.g., over a telephone line, optic fibre, or dedicated cable) or by a wireless connection using a cellular telecommunications system. The router may contain one or more modems or other interfaces. The environment may be any one of: an office, a location, a local network, a location with multiple devices, a household, an apartment, a building, an inside environment, a neighbourhood, a house. The environment may also comprise a finite area surrounding any of the previously mentioned options. For example, an environment may include a house and 1 metre around the perimeter of the house. In another example, an environment may be set by a distance from the router, for example the environment may be 10 metres from the router. It will be appreciated that BLE communication has a finite range, and therefore the environment may be the distance from which a BLE advertisement packet may reach the router. The state of the environment may be a safe state, an unsafe state, or an alert state. In the safe state, it may be determined that the environment only comprises devices which have been identified by the router or access point (AP) before and are considered safe. The devices may have been detected by the router via Bluetooth / BLE. For example, the devices may have previously connected to the router via Wi-Fi, or the devices may have connected to the router via Bluetooth, and the devices may be determined to not be connected to any suspicious activities. For example, it may be determined that the devices have not been present in the environment whilst an intruder is present in the environment, or whilst unauthorised access has been gained to the router (i.e. whilst the router has been hacked). In the safe state, the environment may comprise one or more user-owned devices and may in addition comprise one or more friendly devices. User-owned devices are defined as devices which are frequently present when the user is present in the environment. The user-owned devices may be determined to be frequently absent when the user is absent. For example, a user-owned device may be a smartphone which is frequently carried around by a user. The user may be a household member, e.g. an owner of a house, or a worker in an office building. In other words, the user is associated with (e.g. linked to) the house in which the router is located. The user may be referred to as an approved user. The user may be associated with the house (e.g. approved), by use of a mobile based application installed on one or more of the user’s devices (e.g. a smartphone). In another example, the router may be informed of a number of devices which belong to a user. For example, if a user buys a new device, the router may be informed that this device is a user-owned device. In an alert state, the environment may comprise unknown devices, or devices which have previously been connected to suspicious activities. In an unsafe state, the router may have received a trigger whilst the environment comprises unknown devices or devices which have been previously connected to suspicious activity. The devices which are present in the environment whilst the environment is in an initial state (e.g. safe state) may be identified. Therefore, the identities of the devices which are present during a safe state may be categorised into one or more categories (where the one or more categories are associated with the device being safe), and the category and identities can be stored in a data store. Therefore, it can be determined in the future whether a device is considered to be safe without requiring for the category of the device to be determined at each future time that the device is identified in the environment. Therefore, this results in a more efficient method of identifying devices within an environment at different times, such that the processing power and processing time is reduced. The one or more devices may be identified via one or more wireless internet protocols. For example, the one or more devices may be connected to a router via a Wi-Fi connection or a BLE (Bluetooth Low Energy) connection. Alternatively or additionally the router may perform a scan and receive advertising packets from a device (where the device is configured to connect via BLE), even if such a device may be in a non-connected mode, i.e. the device itself may not be connected to the router, but may send advertising packets over one or more channels. A second set of devices are identified within the environment (e.g. the devices within the environment are identified at a second time, wherein the first set of devices are identified at a first time, and wherein the second time is different to the first time). The data stored is searched to determine whether each of the devices in the second set of devices is found in the data store. If so, it is determined whether the device has a category in the first set of categories (e.g. the device is considered to be known and safe). If the device is not found in the data store, or if it is found with a category which is in a second set of categories (e.g. the device has been marked as unsafe), the environment is considered to be a state which is different to the initial state (i.e. an unsafe state or an alert state). Therefore, by storing identities of devices in the data store with their categories, it can be determined whether each identified device is considered to be safe or not. If the environment is not in the initial state, it can then be determined whether a trigger has been received. For example, if no trigger is received, action may not be taken. However, if a trigger is received, one or more actions may be taken. For example, when the method is used in an alarm system, it may be determined that an unknown or unsafe device is present in the environment. However, this device may be inside or outside of a house or building, whilst being present in the environment. Therefore, it may be decided that in this case no action will be taken, as the device could simply be passing outside of the house, or may belong to a neighbour in an adjoining apartment. Therefore, by considering the presence of a trigger in addition to an unknown or unsafe device, the alarm system is improved. Furthermore, by considering the identity and category of a device, the alarm would not be set off my motion being detected without a device (for example the movement of a pet inside, or the movement of a curtain due to a breeze). The present invention therefore provides an improved method for monitoring an environment and its status, by determining one or more devices within the environment, and considering the category of each of the devices. Such a method can be performed using low energy, and therefore high efficiency, due to the use of BLE. Furthermore, even if the device is in a low power mode, BLE may still be enabled even if Wi-Fi and Bluetooth are not enabled on the device. Therefore, the invention is an improvement over using solely Wi-Fi to determine the identity of one or more devices in an environment. In a first aspect there is provided a method for monitoring an environment, comprising: determining that the environment is in an initial state; identifying, via one or more wireless network protocols, a first one or more of devices located within the environment whilst the environment is in the initial state; categorising each of the first one or more of devices into a first set of one or more categories of devices, and storing the identity and associated category of each of the first one or more of devices in a data store; identifying, via the one or more wireless network protocols, a second one or more of devices located within the environment; searching the data store, and determining whether the identity of each of the second one or more of devices is stored in the data store; if the identity of at least one of the second one or more of devices is not stored in the data store, or if at least one of the identities of the at least one of the second one or more of devices is stored in the data store with a category which is not in the first set of one or more categories, then determining that the environment is in a subsequent state different to the initial state; and in response to receiving a trigger, performing one or more actions if it is determined that the subsequent state is different to the initial state. The first set of one or more categories may one comprise or more of: user owned devices (otherwise referred to as household devices or companion devices), friendly devices (otherwise referred to as frequently detected devices, previously approved devices), safe devices (which can refer to either or both of friendly devices and user-owned devices). The second set of one or more categories may comprise one or more of: unknown devices, previously marked unsafe devices. In one example the one or more wireless network protocols are one or more of Bluetooth Low Energy (BLE), and Wi-Fi. In one example identifying the first and / or second one or more of devices comprises scanning the environment for BLE advertisements transmitted by the respective devices and / or receiving information about the respective device via a Wi-Fi network. In one example the first set of one or more categories comprises a category of user-owned devices and / or a category of friendly devices. In one example the step of categorising a device as user-owned devices comprises using machine learning to determine whether the device is frequently present in the environment when a user is present in the environment. The machine learning may be edgebased learning. The use of machine learning provides the advantage of enabling information which has been gathered about one or more of the first and / or second set of devices to be analysed, and patterns recognized such that decisions can be made. For example, the machine learning may be used to determine the categories of devices. Additionally or alternatively, machine learning may be used to determine the perimeter of the house by determining the locations of the user-owned devices at multiple times. Therefore, it can be determined which devices are located outside of the house, and are therefore neighbouring devices (i.e. not user owned devices). In one example the environment comprises one or more user-owned devices whilst the environment is in the initial state. In one example the step of categorising a device as a friendly device comprises determining the relative location of the device to the environment. In one example the relative signal strength, e.g. a relative signal strength indicator (RSSI), may be used to determine the relative location of the device to the router (i.e. to determine the distance of the device from the router). In another example, the relative location of the device to the router, i.e. the relative location of the device to the environment, may be determined by considering the round-trip times of packets exchanged between the router and the device. In one example, if the identities of all of the second one or more of devices are stored in the data store with a friendly category, determining that the state of the environment is in a subsequent state different to the initial state. For example, if it is determined that no user-owned devices are present in the environment, it may be determined that the environment is not in a safe state. Therefore, if an unknown or unsafe device is also detected, and if a trigger is received, one or more actions may be performed. In some examples, if the environment comprises any user-owned devices as well as the unknown devices, and a trigger is received, a request may be sent to the user-owned device to allow the user to disable an alarm. Alternatively, the alarm may be disabled without requiring user input. Therefore, the user-owned device may be a virtual key, such that the device may be used to disable alarms when it is present in the environment. The user may select one or more devices to be virtual keys. Therefore, the presence of at least one user-owned device may result in the environment being in a different state to the situation in which only friendly devices are present. In one example one or more devices are categorised into a second set of one or more categories of devices if it is determined that a device of the second one or more of devices is not stored in the data store. In one example a trigger is received if any one or more of the following events occur: motion is detected within the environment, a door or window is opened in the environment, glass is broken, heat or sound are detected within the environment. In one example an event is detected within the environment by any one of Wi-Fi sensing, infrared sensors, passive infrared sensors, heat sensors, or microphones. In one example the step of performing the one or more actions comprises any one or more of: activating one or more alarms, issuing a push notification to a mobile application and contacting emergency services. In one example the second one or more of devices comprises devices which are not in the first one or more of devices. A third set of one or more devices may be identified after the second one or more devices has been identified. Some or all of the steps carried out in relation to the second one or more devices may be carried out in relation to the third one or more devices. In this example the data store will comprise the identities of each of the first and second one or more devices. In other words, the data store comprises the identities and associated categories of every device which has previously been identified in the environment. The second one or more devices may comprise all of the first one or more devices. Alternatively, the second one or more devices may comprise some of the first one or more devices. Alternatively, the second one or more devices may comprise none of the devices of the first one or more devices, i.e. none of the second one or more devices are known. The first one or more devices may also be referred to as the first set of one or more devices. The second one or more devices may be referred to as the second set of one or more devices. In one example, two unknown devices may be identified in the second one or more devices. In which case, if a trigger is received, both devices may be categorised into the second set of categories, as the system may not be able to determine which of the two unknown devices was unsafe. An approved user may be able to change a category of a device. Therefore, in such a case where a device is incorrectly categorised in the data store, a user may be able to correct this category. Alternatively, if an incorrectly categorised device is later identified in an environment at the same time as a user-owned device, the category of the incorrectly categorised device may be corrected into a first set of one or more categories (i.e. into a safe category). In another aspect there is provided a system for monitoring an environment, the system comprising: a device comprising: at least one processing unit; and at least one memory encoding computer executable instructions that, when executed by the at least one processing unit, cause the at least one processing unit to perform a method comprising: determining that the environment is in an initial state; identifying, via one or more wireless network protocols, a first one or more of devices located within the environment whilst the environment is in the initial state; categorising each of the first one or more of devices into a first set of one or more categories of devices, and storing the identity and associated category of each of the first one or more of devices in a data store; identifying, via the one or more wireless network protocols, a second one or more of devices located within the environment; searching the data store, and determining whether the identity of each of the second one or more of devices is stored in the data store; if the identity of at least one of the second one or more of devices is not stored in the data store, or if at least one of the identities of the at least one of the second one or more of devices is stored in the data store with a category which is not in the first set of one or more categories, then determining that the environment is in a subsequent state different to the initial state; and in response to receiving a trigger, performing one or more actions if it is determined that the subsequent state is different to the initial state. In one example the system further comprises one or more sensors, wherein the trigger is received if the one or more sensors detect if any one or more of the following events occur: motion is detected within the environment, a door or window is opened in the environment, glass is broken, fire or heat or sound are detected within the environment, or a scheduled event has not occurred within the environment. In one example the device comprises one or more modules configured to enable to device to communicate over Wi-Fi and / or BLE networks. In one example the device is connected to a router or part of a router. BRIEF DESCRIPTION OF DRAWINGS The present invention may be put into practice in a number of ways and embodiments will now be described by way of example only and with reference to the accompanying drawings, in which: Figure 1 shows an environment having a status; Figure 2 shows an environment having a different status; Figure 3 shows an environment having a different status; Figure 4 shows a flowchart of a method for monitoring an environment; Figure 5 shows a flowchart of further example steps in the method of figure 4; Figure 6 shows a schematic diagram of a router for performing the method of figure 4; and Figure 7 shows a schematic diagram of a system for performing the method of figure 4. It should be noted that the figures are illustrated for simplicity and are not necessarily drawn to scale. Like features are provided with the same reference numerals. DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS Hereinafter, examples of the disclosure are described with reference to the accompanying drawings. However, it should be appreciated that the disclosure is not limited to the described examples, and all changes and / or equivalents or replacements thereto also belong to the scope of the disclosure. The same or similar reference denotations may be used to refer to the same or similar elements throughout the specification and the drawings. The following description is directed to certain implementations for the purposes of describing innovative aspects of various embodiments. However, a person having ordinary skill in the art will readily recognize that the teachings herein can be applied in a multitude of different ways. The described implementations may be implemented in any device, system, or network that is capable of transmitting and receiving radio frequency (RF) signals according to any communication standard, such as any of the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards (including those identified as Wi-Fi technologies), the Bluetooth standard, and Bluetooth Low Energy (BLE). The term Wi-Fi is used here to refer to any local area wireless technology, including but not limited to wireless local area networks based on the IEEE 802.11 standards. Figure 1 illustrates an example environment 100, comprising one or more devices 101 and 103. In this example, the devices may either be located within a house, shown by devices 101 in figure 1, or may be located outside of the house but in the vicinity of the house, shown by devices 103 in figure 1. It will be appreciated that although the embodiments described herein are within the example of a house being within the environment, the same inventive concepts and techniques apply to examples wherein the environment comprises a building, or wherein the environment is defined by an area comprising one or more devices. For example, the environment may be any area or network that comprises one or more devices. The environment may be any one of: an office, a location, a local network, a location with multiple devices, a household, an apartment, a building, an inside environment, a neighbourhood, a house. The environment may comprise devices which are located within the building or within a finite distance from the building. For example, the environment may be defined by a range from the router 110. For example, the environment may be defined as 20 meters from the router. In another example the environment may be defined as a distance, e.g. 10 meters, from the perimeter of a house or building in which the router is located. The devices which are located outside of the house but nearby to the house may be known as neighbouring devices. Neighbouring devices are a subset of friendly devices. In other words, neighbouring devices are found in the category of friendly devices. The environment may further comprise a router 110, wherein the router is configured to connect to one or more wireless devices over one or more networks. The router may be otherwise referred to as consumer-premises equipment (CPE). The router may be a home broadband router. For example, the router may be configured to identify one or more devices within a Wi-Fi network, or within a BLE network. For example, the router may be configured to connect to one or more devices using one or more wireless network protocols (i.e. communication protocols), such as BLE and / or Wi-Fi. The router may comprise any one or more of: a Wi-Fi communication module or a BLE communication module, or an loT module (where the loT module is configured to scan for BLE advertisement packets). Alternatively, the router may be connected to a Wi-Fi communication module and / or loT communication module. The router may be configured to scan the environment for BLE advertisements by listening to a specific channel during a scan window. The router may iterate scanning over all advertising channels by switching channels after a period called the scan interval. The router 110 may also have broadband modem functionality and components, including a cable interface to a telephone system, for example. A mobile device 101 can initiate a Bluetooth connection between the mobile device 101 and the router 110 (e.g., Bluetooth pairing). The Bluetooth pairing can be permanent so a Bluetooth or BLE connection can be made automatically whenever the mobile device 101 is in Bluetooth range of the router 110. The router 110 is configured to determine the identities of one or more devices using information received from BLE packets, and optionally from Wi-Fi signals. The payload of BLE advertisements consists of Advertising Data (AD). BLE compatible devices include AD to define, e.g., their device name, address, the list of offered services (such as sound or heart rate sensor), or data related to its specific manufacturer. Each AD is identified by its universally unique identifier (UUID), defined in the BLE standard. Therefore, the router is able to identify one or more BLE devices by using the information received via advertising data. The router comprises a data store, in which the identity of detected devices is stored. It can also be determined whether the device is connected to the router, for example using WiFi, and therefore the router can also store such connection information within the data store, such that it can be determined whether a device has previously connected to the router via Wi-Fi. The one or more devices may be categorised by the router 110. The one or more devices may be categorised into a first set of categories or into a second set of categories (where it will be appreciated that there may be more sets of categories in other examples). The categories within the first set of categories may be considered to be safe categories, i.e. the devices which are categorised into the first set of categories may be safe devices. The categories within the second set of categories may be considered to be unsafe categories, i.e. the devices which are categorized into the second set of categories may be unsafe devices. The router may store the category of a device with the identity of the device, i.e. the router associates an identity of a device with its category such that the router can determine the category of the device when the device is detected in the environment at a later time. It may be determined that a device is a safe device if the device has previously been connected to the router 110, or if it is determined that the device is frequently located within the environment, even if it is not located within the house / building itself. For example, it may be determined that a device is a friendly device (which could be a neighbouring device) if the device is frequently detected within the environment by the router, even if the device is not located within the house (otherwise referred to as household or building) itself. A device may therefore be a friendly device whether it is located within or outside the house. For example, if the device is a wireless speaker which is located within the house it will be frequently detected by the router. Alternatively, a guest may often visit the house with a device, and therefore the device may be determined to be safe as it may be determined that such a device is present whilst a household member (otherwise referred to as a user) is in the house, and therefore it can be determined that the guest’s device is safe rather than being an intruder’s device (i.e. an unsafe device). Additionally, if a third-party lives in a neighbouring house and has a device, the router may frequently detect the device even though it is not in the house, and therefore the router can determine that the device is friendly. A device may be determined to be a safe device if the device is determined to be a user-owned device, i.e. if the device is determined to be present when a user is present. For example, it may be determined (or the router may be notified) that a smartphone or smartwatch is typically located within the environment (i.e. within the house, otherwise known as the home premise) when a user is at home. Machine learning, for example edgebased learning, may be used to determine whether a device is a neighbouring device, or whether the device is a friendly device, or whether the device is a user-owned device. Edge based learning can be used to determine the frequency of a device’s presence, and a correlation between a user’s presence and a device’s presence. The edge-based learning may use received signal strength (RSS), e.g. it may use a received signal strength indicator (RSSI), to determine the distance of a device from the router. The edge-based learning may additionally or alternatively use round-trip time of packets exchanged between the device and the router to determine the distance of a device from the router. Based on the determined distance, it can be determined whether a device is located within a household, or whether the device is located in a neighbouring household (i.e. a neighbouring flat), or whether the device is detected as a third party walks by the household. For example, it may be determined whether the device is only temporarily within the environment, or whether the device is outside of the household but is frequently detected. It may be determined that the device has been detected previously, and this presence has not been associated with any detected movements (i.e. the device is not associated with an intruder), and therefore the device can be categorised as a neighbouring device. A user may provide information about the dimensions of the house, i.e. to determine the perimeter of the house, such that it can be determined whether a device is located within the house or outside of the house. Alternatively or additionally, the dimensions of the house may be determined using edge based learning based on collected information about where user-owned devices are detected. For example, it can be determined whether the house has multiple levels (i.e. multiple stories or floors) or whether the building is an apartment, based on the location of user-owned devices, and their distance from the router. BLE may have a range of between 20 and 100 meters, and therefore devices which are on different levels of the building may be identified as either user-owned devices or neighbouring devices, depending on the perimeter of the house or apartment. The dimensions (i.e. the perimeter of the house) can be used in the determination of whether a device is a user-owned device (a device which is frequently detected within the house while a user is in the house), a friendly device (i.e. a known device which may frequently be located inside or outside the house, but not a user-owned device) or whether the device is a neighbouring device (a friendly device which is frequently detected outside of the house, but is not frequently detected within the house). It may be determined that the device is an unknown device (otherwise referred to as an unsafe device) by determining that the device has not been detected or connected to the router previously, i.e. the router has not stored any identification information for the device. Alternatively the device may be determined to be an unknown device if the router has stored the identity of the device, i.e. it recognises the identity of the device, but the device has previously been categorised as unsafe. The one or more devices may be any suitable device which is in communication with the router. The devices may be wearable devices (e.g. smart watches or fitness trackers), smartphones, wireless headphones, wireless speakers, smart home devices (e.g. cameras, smart TVs), etc. In the embodiment shown in figure 1, the devices 101 and 103 are each in the first set of categories, labelled as category A in the figure. In other words, the devices are all safe devices. It will be appreciated that there may be one or more devices present in the environment, and the number of devices shown in figure 1 is for exemplary purposes only. In one example there may be only devices present in the house, or there may be devices present both in the house and outside of the house. The environment can be categorised as being in a safe state as there are no unknown devices present, and there are no devices present which have been categorised as unsafe. One of the devices 101 and 103 may be a user-owned device, and therefore the other devices present in the house at the same time as the user-owned device may be categorised by the router as being friendly devices, and the router may store the identity of the device and its category association within its data store. Figure 2 shows a second example of an environment 200, in which the device comprises a second set of devices. The environment 200 may be the environment 100 at a later, or different, time. The second set of devices may comprise some or all of the devices present in the first set of devices. The environment 200 may comprise no user-owned devices. The environment 200 may further comprise a device 205 which is determined to be an unknown or unsafe device, and therefore is categorised into a second set of categories, shown in figure 2 as category B. The device 205 may instead be located outside of the house, and may result in the same outcome. The other devices 201 and 203 are determined to be user-owned devices or friendly devices, i.e. the devices are safe devices. The device 205 may be identified as a device which has been previously categorised as unsafe, e.g. the device has previously been associated with an intruder. The environment 200 may have a different state to the situation in which the environment only comprises user-owned and / or friendly devices. If the environment does not comprise a user-owned device, the environment may be in an unsafe state, or may be in an alert state. If there is no motion or other trigger detected in the environment, the router may determine that no action needs to be taken unless a trigger is received, as the device may simply be an unknown device passing by, or a new device owned by a neighbouring user. Alternatively, or additionally, if the environment comprises a user-owned device, the user may inform the router via an interface that the environment is in a safe state, or it may be determined that the environment is in a safe state (without requiring user input) due to the presence of the user-owned device within the environment. Figure 3 shows another example environment 300.. The environment 300 may be the same building or house as the environment described in relation to figures 1 and 2. For example at a first time the environment may be in a safe state as described in relation to figure 1, or the environment may be in an alert safe as described in relation to figure 2. At a later time, the environment may be in an unsafe state, as will be described in relation to figure 3. As described in relation to environment 200, the environment comprises a device which is an unknown or unsafe device. In this example the environment does not comprise any user-owned devices, or a user has not informed the router that the environment is in a safe state, and therefore the environment remains in an unsafe state, and the router also has received a trigger due to motion being detected within the house. In this example, the motion is detected due to an intruder 307 moving within the house. Therefore, as the environment is in an unsafe state and a trigger has been received, one or more actions may be performed. In this embodiment, an alarm 309 is located within the environment (e.g. within the house) and therefore the action may be to initiate an alarm. In this example in which a trigger is received due to motion being sensed, the motion may be sensed by the router using Wi-Fi to detect motion events, i.e. using Wi-Fi sensing. In such an example, it is determined whether propagation of Wi-Fi waves are disrupted, and therefore whether there is motion within the house. The house or building may comprise one or more devices which extend the range of the Wi-Fi signals (e.g. Wi-Fi extenders, or Wi-Fi boosters) to enable motion to be detected throughout the house. In other examples the motion may be sensed using a motion sensor. The house may additionally or alternatively comprise any one or more of: infrared sensors, passive infrared sensors, heat sensors or microphones, or any other suitable means for detecting changes within an environment, i.e. for initiating a trigger. Figure 4 illustrates a method for monitoring an environment according to an embodiment of the invention. The method may be performed by a router, for example by a broadband router, or it may be performed by a system of devices, wherein one or more communication modules (e.g. a Wi-Fi module and / or an loT module) are connected to a router. In the first step 410, it is determined that the environment is in an initial state. As described herein, the initial state may be a safe state, wherein no unknown devices, or devices which have been categorised as unsafe, are present. The initial state may be either determined by the system itself, for example based on no movement being detected within an environment. Alternatively, the safe state may be determined by a user who can inform the system, via an interface (e.g. a mobile based application, or a web interface, or a button interface located on the router itself), that the environment is in a safe state such that it is known that all devices present in the environment are safe devices. At step 420, a first one or more of devices located within the environment whilst the environment is in the initial state are identified. In other words, it is determined which (if any) devices are present in the environment whilst the environment is in an initial state, and the identities of each of the devices are determined. It will be appreciated that in other examples, there may be only one device identified. The first one or more of devices are identified via one or more wireless network protocols. For example, the one or more devices may be identified by one or more advertising packets being received, wherein the advertising packets provide information which is sufficient to identify the device. In another example, the first devices may be identified via Wi-Fi wherein the device identifies itself to the Wi-Fi network using a unique network address, i.e. using Media Access Control (MAC) address. Therefore, the one or more devices can be identified either over the BLE networks and / or over the Wi-Fi network. At step 430, the first devices are categorised into a first set of one or more categories of devices. The devices may be categorised into the same category, or the devices may be categorised into separate categories. The devices may be categorized based on their identities, where the device may have been previously identified and categorised in the environment. Additionally or alternatively, the devices may be categorised based on their relative location to the router. For example, it may be determined that one or more of the devices are located outside of a house (i.e. the device neighbours the house, or the device is located near to a predetermined perimeter of the house). Such a determination may be determined using the received signal strength (RSS) of the signals received at the router, e.g. the received signal strength indicator (RSSI) of the signals may be used. Alternatively, the relative location of a device to the router may be determined by measuring the round-trip time of packets which are exchanged between the router and the device. Additionally or alternatively, the devices may be categorised using machine learning, e.g. edge based learning, wherein it can be determined that one or more of the identified devices are frequently present within the environment when a user is located within the environment. The presence of a user may be determined using motion sensing and / or by determining of a pattern of a user’s movements. For example, if a device is not present within a house during a weekday, but is present during the night-time, it may be determined that such a device is a user-owned device which is present in the environment when a user is located within the house. Alternatively, in the example where the environment comprises an office building, it may be determined that a device is a user-owned device if the device is located within the building during the day, but is not present during nighttime hours or at the weekend. Machine learning may be used to determine that one or more devices are neighbouring devices, based on distance of the device from the router (determined using the received signal strength indicator) to determine that the device is not located within the house or building. It may also be determined that the device is present even when there is not a user within the house, which may be determined using motion sensing. For example, a device may belong to a neighbour and therefore the device may frequently be within the environment but the presence of the device is not linked to motion within the house. Alternatively, a device may belong to a user who frequently passes by the house, but does not enter the house, in which case it can be determined that the device is not located within the environment for a long period of time (e.g. the router could determine whether the device is still located within the environment at a second time). Machine learning may use any information that is received about the identity of the device, or the movements of the device, or the location of the device, to categorise the device into one of the first or second set of categories. The determined identity of each of the identified first one or more of devices, and each of their associated (i.e. assigned) categories, may be stored in a data store (e.g. a database). The identity and category of each device may be associated (i.e. linked or related) such that when a device is identified in future, it is possible to determine the category of the device based on its identity. Storing the identities and categories of devices is an iterative (i.e. cumulative) process, such that each time a device is identified, its identity and category may be stored in the same datastore, such that the datastore comprises identities of previously identified devices. The datastore may be located at the router, or may be located on a remote sever (e.g. the data may be stored in the cloud). At step 450 a second one or more of devices are identified within the environment. In other words, a second one or more of devices may be detected within the environment and identified. In other words, a second one or more of devices may be determined to be present within an environment, and each of the devices that are present may be identified. It will be appreciated that in some embodiments only one device may be identified within the environment. The second one or more of devices may comprise none of, some of, or all of the first one or more of devices. If no devices are present, the method does not continue to step 460. At step 460 the data store is searched, and it is determined whether the identity of each of the one or more of devices is stored in the data store. In other words, the data store is searched for the identities of each of the second one or more of devices, i.e. the identity of the device is compared to the list of identified devices stored in the data store. As described herein, the identities of the devices which are stored within the data store also are each associated with a category of the device. Therefore, when an identity of one of the second one or more of devices is found in the data store, the associated category of the particular device may also be found from the data store. If the identity of at least one of the second one or more of devices is not stored within the data store, the method proceeds to step 480. If the at least one of the second one or more of devices is not stored within the data store, a user may be notified and can mark a device as a safe device, i.e. the user may manually categorise the device into one of the first set of one or more categories, and the identity and category may be stored in the data store. Otherwise, the identity of the device may be stored in the data store as an unsafe device, for future reference. If it is determined that the identity of at least one of the one or more of second devices is stored in the data store, the method proceeds to step 470. At step 470 it is determined whether the device has a category which is not in the first set of one or more categories. If so, then the method proceeds to step 480. In other words, if an identity of a device is found to be stored in the data store, it is determined whether the device is categorised into the first set of one or more categories. Then, if the device is not found to be categorised into the first set of one or more categories, the method proceeds to step 480. If at step 470, it is determined that all of the devices in the second one or more of devices are found in the data store and are categorised in the first set of one or more categories, the method may stop. In other words, no action may be taken after step 470. Optionally, it may be determined that the environment is in a subsequent state which is the same as the initial state, e.g. the environment is in a safe state. Further optionally, the method may continue to step 550 of the embodiment of figure 5, as will be described herein. If the identity of the device is stored in the data store with a category which is in the set of one or more categories, no further action is taken (i.e. the method of this example stops after step 460). In this example, each of the categories within the first set of one or more categories are safe categories. In other words, there are no devices present which have been marked as unsafe, i.e. the identified devices have either been categorised as user-owned devices, or friendly devices (including devices described herein as neighbouring devices or known devices). At step 480 it is determined that the environment is in a subsequent state to the initial state, wherein it is determined that the subsequent state is different to the initial state. For example, if the initial state is a safe state, the subsequent state may be an alert state, or an unsafe state due to an unknown or unsafe device being detected within the environment. In one example, if the environment is in an alert or unsafe state due to an unknown or unsafe device being detected within the environment, being wireless connected (e.g. latched on) to the router, a wider system (e.g. a home monitoring system) may be set to an armed mode, i.e. one or more alarms may be activated. At step 490 a trigger is received, and one or more actions are performed if it is determined that the subsequent state is different to the initial state. The trigger may be received based on a detected change in the environment. For example, motion may be detected, sound may be detected, a change in lighting may be detected, a door or window may be opened, a change in temperature may be detected, or it may be determined that glass has been broken. It will be appreciated that the trigger may be received based on different changes being detected. Therefore, the environment may comprise any one or more of: Wi-Fi-sensing capabilities, infrared sensors, passive infrared sensors, heat sensors or microphones, or any other suitable means for detecting changes within an environment. Based on the trigger being received, and the unknown or unsafe device being present, the environment’s state may be determined to be an unsafe state. Therefore, one or more actions may be performed. The one or more actions may be any one or more of: activating one or more alarms, issuing a push notification to a mobile application, calling a telephone number, initiating recording on one or more cameras, contacting emergency services. Alternatively, if it is determined that a user-owned device is also present in the environment, either by being identified using BLE or due to the user-owned device being connected to the router via Wi-Fi, it may be determined that the unknown device is a safe device. In other words, one or more user-owned devices may be selected to be virtual keys, such that if any of the selected user-owned devices are present in the environment, the environment is determined to be in a safe state even if an unknow device is present. Alternatively, if a selected user-owned device (i.e. a virtual key) is detected at the environment after the one or more actions have been performed (e.g. after an alarm has been initiated), a further action may be performed (e.g. to turn off the alarm). If any of the selected user-owned device(s) are present whilst a previously marked unsafe device is present, the user-owned device may be notified, or the method may continue to step 490, such that one or more actions are performed. After step 490, the method may optionally continue to step 550 of figure 5. Figure 5 illustrates further steps which may be combined with the method described in relation to figure 5, according to an embodiment of the invention. After either steps 470 or 490, i.e. either after it has been determined that all of the devices in the second one or more of devices are categorised in a first set of one or more categories, or after one or more actions have been performed, step 550 may be performed. At step 550, a third one or more of devices are identified via one or more wireless network protocols. Such a step has the same aspects and considerations as step 450 described in relation to figure 4. At step 560 the data store may be searched to determine whether the identity of each of the third one or more of devices are stored in the data store. The data store will include the devices identified in the method of figure 4. For example, if a device was found to be unknown, and was not marked as safe by a user (i.e. it was categorised as being in the second set of categories), the data store will contain the identity and category of the device. Therefore, the data store contains the identities and categories of all of the devices which have previously been identified (i.e. detected and identified). If the identity of at least one of the third one or more of devices is not stored within the data store, the method proceeds to step 580. If it is determined that the identity of at least one of the one or more of second devices is stored in the data store, the method proceeds to step 570. At step 570 it is determined whether the device has a category which is not in the first set of one or more categories. If so, then the method proceeds to step 580. In other words, if an identity of a device is found to be stored in the data store, it is determined whether the device is categorised into the first set of one or more categories. Then, if the device is not found to be categorised into the first set of one or more categories, the method proceeds to step 480. If at step 570, it is determined that all of the devices in the third one or more of devices are found in the data store and are categorised in the first set of one or more categories, the method may stop. In other words, no action may be taken after step 570. Optionally, it may be determined that the environment is in a subsequent state which is the same as the initial state, e.g. the environment is in a safe state. If the identity of the device is stored in the data store with a category which is in the set of one or more categories, no further action is taken (i.e. the method of this example stops after step 560). In this example, each of the categories within the first set of one or more categories are safe categories. In other words, there are no devices present which have been marked as unsafe, i.e. the identified devices have either been categorised as user-owned devices, or friendly devices (including devices described herein as neighbouring devices or known devices). At step 580 it is determined that the environment is in a subsequent state to the initial state, where this subsequent state may be referred to as a third state for clarity, wherein it is determined that the third state is different to the initial state. In one example, it may be determined whether the third state of the environment is in a different state to the state determined after the identification of the second one or more of devices (also referred to as the second state for clarity purposes). Therefore, one or more actions may be carried out, as described herein, where such actions may differ depending on whether the third state is different to or equal to the second state. At step 590 a trigger is received, and one or more actions are performed if it is determined that the subsequent state is different to the initial state, as described in relation to figure 4. Based on the trigger being received, and the unknown or unsafe device being present, the environment’s state may be determined to be an unsafe state. Therefore, one or more actions may be performed, as described in relation to figure 4. Therefore, the method described herein is an iterative process and may the identification steps and the proceeding steps may be repeated multiple times. For example, the steps may be repeated at predetermined intervals, wherein the intervals may differ based on the time of the day, or based on whether a user is in the house, or whether a user is on holiday (i.e. the building or house is empty for an extended period of time). Although the invention has been described in relation to home security, the inventive techniques described herein could be used for other purposes. In one use, the invention could be used to determine whether a pattern, or schedule is being followed. For example, it may be expected that an approved person is present within the house at predetermined times, and therefore their device may be put into a category different to the first set of categories (i.e. different to the user-owned devices and friendly devices). Therefore, if it is determined that the approved person’s device is present in the environment, and a trigger is received (i.e. motion is detected), a notification may be issued to inform a user that either a schedule has been met if the approved person is in the environment at the expected time, or alternatively to inform a user that the approved person is in the environment at an incorrect time. Furthermore, if an unknown device or unsafe device is detected, the user or the approved person may be notified, as in the other embodiments described herein. Furthermore, if the approved person’s device is not detected at the expected time, i.e. the second set of devices only comprises neighbouring devices passing through the environment, the environment may be determined to be in an incorrect state (i.e. the schedule has not been met). In which case, a tigger may be received based on the schedule not being met, and a user may be notified. In another use, the invention could be used for home automation. For example, it may be determined that only neighbouring and / or friendly devices are present in the environment (i.e. no user-owned devices are present in the environment), and therefore the state of the environment may be considered to be unoccupied. In such an example, the initial state of the environment may be occupied, and the first set of one or more of devices may comprise only user-owned devices. Therefore, at a later time, on identification of a nonuser owned device, for example a neighbouring device or friendly device, the environment may be analysed to determine whether any user-owned devices are present. If no user-owned devices are present, one or more actions may be taken, for example to turn off lighting and / or heating in the house. The one or more actions may be carried out after a trigger is received, for example if a door is locked after a user leaves the house and it is determined that there are no other users present in the house, the lighting or heating may be switched off. In another example, if a schedule determines that the heating or lighting should be switched on, but it is determined that no user-owned devices are present in the environment, the schedule may be ignored, such that the heating and / or lighting are not turned on. Figure 6 illustrates a device 610 for monitoring an environment, wherein the device has at least one data store 616, at least one processing unit 620, and at least one memory 618. As described herein, the data store may instead be located within a remote network, instead of being located on the device. The system is configured to carry out the invention as described herein. In particular, the device may comprise one or more modules configured to communicate over Wi-Fi and / or BLE networks. The one or more modules may be connected to the device or be a part of the device. The device may be a router. The system may further comprise one or more sensors (not shown in figure 6), wherein the trigger is received if the one or more sensors detect if any one or more of the following events occur: motion is detected within the environment, a door or window is opened in the environment, glass is broken, fire or heat or sound are detected within the environment, or a scheduled event has not occurred within the environment. As shown in Figure 7, the system 700 includes a mobile device 701 that has a number of components including communication interfaces 720, system circuitry 730, input / output (I / O) circuitry 740, display circuitry and interfaces 750, and a datastore 770. The system circuitry 720 can include one or more processors or CPUs 780 and memory 790. The system circuitry 730 may include any combination of hardware, software, firmware, and / or other circuitry. The system circuitry 730 may be implemented, with one or more systems on a chip (SoC), application specific integrated circuits (ASIC), microprocessors, and / or analogue and digital circuits. The router 710 is shown as having at least two communication protocols or channels with the mobile device 701. For example, these may be Wi-Fi (e.g., IEEE 802.11 and variants) and Bluetooth, for example. The mobile device 701 may also communicate with the external server 710 over a different communication protocol (preferably cellular). These communications may be two-way, as shown by the arrows. The mobile device 701 may run an operating system such as iOS or Android, for example. The mobile device 701 may run one or more mobile applications, such as one used to view the one or more devices which are connected to the router, or to view and change the categories assigned to each of the one of more devices which are saved in the datastore. The display circuitry may provide one or more graphical user interfaces (GUIs) 760 and the I / O interface circuitry 740 may include touch sensitive or non-touch displays, sound, voice or other recognition inputs, buttons, switches, speakers, sounders, and other user interface elements. The I / O interface circuitry 740 may include microphones, cameras, headset and microphone input / output connectors, Universal Serial Bus (USB) connectors, and SD or other memory card sockets. The I / O interface circuitry 740 may further include data media interfaces (e.g., a CD-ROM or DVD drive) and other bus and display interfaces. The memory 790 may include volatile (RAM) or non-volatile memory (e.g., ROM or Flash memory). The memory may store the operating system 792 of the computer system 700, applications or software 794, dynamic data 796, and / or static data 798. The datastore or data source 770 may include one or more databases 772, 774 and / or a file store or file system, for example. The method and system may be implemented in hardware, software, or a combination of hardware and software. The method and system may be implemented either as a server comprising a single computer system or as a distributed network of servers connected across a network. Any kind of computer system or other electronic apparatus may be adapted to carry out the described methods. In an example implementation of system 700, a mobile application is installed on the mobile device 701. The mobile device 701 has at least Wi-Fi, cellular (e.g., 2G, 3G, 4G, 5G, 6G, etc.) and Bluetooth (e.g., BLE) communication interfaces. The router 710 also has one or more Wi-Fi interfaces or radios and Bluetooth connectivity, so that it can connect wirelessly to the mobile device 701 over different communication protocols. The router 710 also has broadband modem functionality and components, including a cable interface to a telephone system, for example. The mobile device can initiate a Bluetooth connection between the mobile device 701 and the router 710 (e.g., Bluetooth pairing). The Bluetooth pairing can be permanent so a Bluetooth or BLE connection can be made automatically whenever the mobile device 701 is in Bluetooth range of the router 710. It will be appreciated that the inventive concepts described herein may be applied to any use which could be improved by determining which devices are present in an environment. It will be appreciated that a number of actions and outcomes could be performed based on such information, and such actions are not limited to the examples provided herein. The methods described herein may be implemented with computer system configurations including hand-held devices, microprocessor systems, microprocessor- based or programmable consumer electronics, minicomputers, mainframe computers and the like. The embodiments can also be practiced in distributed computing environments, where tasks are performed by remote processing devices that are linked through a network. The computer system may include a processor, such as a central processing unit (CPU). The processor may execute logic in the form of a software program. The computer system may include a memory including volatile and non-volatile storage medium. The different parts of the system may be connected using a network (e.g. wireless networks and wired networks). The computer system may include one or more interfaces. The computer may contain a suitable operating system such as UNIX (including Linux) or Windows (RTM), for example. Certain embodiments can also be embodied as computer-readable code on a non-transitory computer-readable medium. The computer readable medium may be any data storage device than can store data, which can thereafter be read by a computer system. Examples of the computer readable medium include hard drives, network attached storage (NAS), read-only memory, random-access memory, CD-ROMs, CD-Rs, CD-RWs, magnetic tapes, and other optical and non-optical data storage devices. The computer readable medium can also be distributed over a network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion. Although embodiments according to the disclosure have been described with reference to particular types of devices and applications (particularly augmented reality devices) and the embodiments have particular advantages in such case, as discussed herein, approaches according to the disclosure may be applied to other types of device and / or application. Each feature disclosed in this specification, unless stated otherwise, may be replaced by alternative features serving the same, equivalent or similar purpose. Thus, unless stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features. All of the aspects and / or features disclosed in this specification may be combined in any combination, except combinations where at least some of such features and / or steps are mutually exclusive. In particular, the preferred features of the disclosure are applicable to all aspects and embodiments of the disclosure and may be used in any combination. Likewise, features described in non-essential combinations may be used separately (not in combination). It will be appreciated that there is an implied “about” prior to temperatures, concentrations, times, pressures, flow rates, cross-sectional areas, voltages, currents, etc. discussed in the present teachings, such that slight and insubstantial deviations are within the scope of the present teachings. Furthermore, values referred to as being “equal” may in fact differ by less than a threshold amount. The threshold amount may be 5%, for example. The threshold may also be greater than 5% (e.g., 10%, 20% or 50%) or less than 5% (for example, 2% or 1 %), depending on the context. As used herein, including in the claims, unless the context indicates otherwise, singular forms of the terms herein are to be construed as including the plural form and vice versa. For instance, unless the context indicates otherwise, a singular reference herein including in the claims, such as “a” or “an” (such as a component) means “one or more” (for instance, one or more components). Throughout the description and claims of this disclosure, the words “comprise”, “including”, “having” and “contain” and variations of the words, for example “comprising” and “comprises” or similar, mean “including but not limited to”, and are not intended to (and do not) exclude other components. Also, the use of “or” is inclusive, such that the phrase “A or B” is true when “A” is true, “B is true”, or both “A” and “B” are true. The use of any and all examples, or exemplary language (“for instance”, “such as”, “for example" and like language) provided herein, is intended merely to better illustrate the disclosure and does not indicate a limitation on the scope of the disclosure unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the disclosure. The terms “first” and “second” may be reversed without changing the scope of the invention. That is, an element termed a “first” element (e.g., a first component) may instead be termed a “second” element (e.g., a second component) and an element termed a “second” element (e.g., a second component) may instead be considered a “first” element (e.g. a first component). Any steps described in this specification may be performed in any order or simultaneously unless stated or the context requires otherwise. Moreover, where a step is described as being performed after a step, this does not preclude intervening steps being performed. It is also to be understood that, for any given component or embodiment described herein, any of the possible candidates or alternatives listed for that component may generally be used individually or in combination with one another, unless implicitly or explicitly understood or stated otherwise. It will be understood that any list of such candidates or alternatives is merely illustrative, not limiting, unless implicitly or explicitly understood or stated otherwise. In this detailed description of the various embodiments, for the purposes of explanation, numerous specific details are set forth to provide a thorough understanding of the embodiments disclosed. One skilled in the art will appreciate, however, that these various embodiments may be practiced with or without these specific details. Furthermore, one skilled in the art can readily appreciate that the specific sequences in which methods are presented and performed are illustrative and it is contemplated that the sequences can be varied and still remain within the scope of the various embodiments disclosed herein. All literature and similar materials cited in this application, including but not limited to patents, patent applications, articles, books, treaties and internet web pages are expressly 5 incorporated by reference in their entirety for any purpose. Unless otherwise described, all technical and scientific terms used herein have a meaning as is commonly understood by one of ordinary skill in the art to which the various embodiments described herein belongs.

Claims

1. A method for monitoring an environment, comprising:determining that the environment is in an initial state;identifying, via one or more wireless network protocols, a first one or more devices located within the environment whilst the environment is in the initial state;categorising each of the first one or more devices into a first set of one or more categories of devices, and storing the identity and associated category of each of the first one or more devices in a data store;identifying, via the one or more wireless network protocols, a second one or more devices located within the environment;searching the data store, and determining whether the identity of each of the second one or more devices is stored in the data store;if the identity of at least one of the second one or more devices is not stored in the data store, or if at least one of the identities of the at least one of the second one or more devices is stored in the data store with a category which is not in the first set of one or more categories, then determining that the environment is in a subsequent state different to the initial state; andin response to receiving a trigger, performing one or more actions if it is determined that the subsequent state is different to the initial state.

2. A method according to claim 1 wherein the one or more wireless network protocols are one or more of Bluetooth Low Energy (BLE), and Wi-Fi.

3. A method according to claim 2 wherein identifying the first and / or second one or more of devices comprises scanning the environment for BLE advertisements transmitted by the respective devices and / or receiving information about the respective device via a Wi-Fi network.

4. A method according to any preceding claim wherein the first set of one or more categories comprises a category of user-owned devices and / or a category of friendly devices.

5. A method according to any preceding claim wherein the step of categorising a device as user-owned devices comprises using machine learning to determine whether the device is frequently present in the environment when a user is present in the environment.

6. A method according to any of claims 4 or 5 wherein the environment comprises one or more user-owned devices whilst the environment is in the initial state.

7. A method according to any of claims 4 to 6 wherein the step of categorising a device as a friendly device comprises determining the relative location of the device to the environment.

8. A method according to claim 7 wherein if the identities of all of the second one or more of devices are stored in the data store with a friendly category, determining that the state of the environment is in a subsequent state different to the initial state.

9. A method according to any preceding claim further comprising categorising one or more devices into a second set of one or more categories of devices if it is determined that a device of the second one or more of devices is not stored in the data store.

10. A method according to any preceding claim wherein a trigger is received if any one or more of the following events occur: motion is detected within the environment, a door or window is opened in the environment, glass is broken, heat or sound are detected within the environment.

11. A method according to claim 10 wherein an event is detected within the environment by any one of Wi-Fi sensing, infrared sensors, passive infrared sensors, heat sensors, or microphones.

12. A method according to any preceding claim wherein the step of performing the one or more actions comprises any one or more of: activating one or more alarms, issuing a push notification to a mobile application and contacting emergency services.

13. A method according to any preceding claim wherein the second one or more of devices comprises devices which are not in the first one or more of devices.

14. A wireless network system for monitoring an environment, comprising:a device comprising:at least one processing unit; andat least one memory encoding computer executable instructions that, when executed by the at least one processing unit, cause the at least one processing unit to perform a method comprising:determining that the environment is in an initial state;identifying, via one or more wireless network protocols, a first one or more of devices located within the environment whilst the environment is in the initial state;categorising each of the first one or more of devices into a first set of one or more categories of devices, and storing the identity and associated category of each of the first one or more of devices in a data store;identifying, via the one or more wireless network protocols, a second one or more of devices located within the environment;searching the data store, and determining whether the identity of each of the second one or more of devices is stored in the data store;if the identity of at least one of the second one or more of devices is not stored in the data store, or if at least one of the identities of the at least one of the second one or more of devices is stored in the data store with a category which is not in the first set of one or more categories, then determining that the environment is in a subsequent state different to the initial state; andin response to receiving a trigger, performing one or more actions if it is determined that the subsequent state is different to the initial state.

15. A system according to claim 14 further comprising one or more sensors, wherein the trigger is received if the one or more sensors detect if any one or more of the following events occur: motion is detected within the environment, a door or window is opened in the environment, glass is broken, fire or heat or sound are detected within the environment, or a scheduled event has not occurred within the environment.

16. A system according to any of claims 14 or 15 wherein the device comprises one or more modules configured to enable to device to communicate over Wi-Fi and / or BLE networks.

17. A system according to any of claims 14 to 16, wherein the device is connected to a router or part of a router.31