EP-4740195-A1 - METHOD FOR OPTIMIZATION OF SENSOR NETWORK PLACEMENT

Abstract

Method for installing and/or optimizing a sensor network comprising a plurality of sensors, said method comprising the steps of receiving environmental data related to an area to be sensed, preferably an area containing a luminaire, and optionally constraint data related to the sensor network, identifying one or more suitable applications configured for using data sensed by one or more of the plurality of sensors of the sensor network, determining at least one characteristic or optimized characteristic of the sensor network based on the environmental data, the identified one or more applications, and optionally on the constraint data. A computer system or platform or infrastructure and an edge device corresponding to the method is also provided.

Inventors

• BANDEIRA, Lourenço

Assignees

• Schreder Iluminaçao SA

Dates

Publication Date

20260513

Application Date

20240704

Claims (20)

1. 1. Method for installing and/or optimizing a sensor network (200) comprising a plurality of sensors (201a, 201b, 201c, 201d), said method comprising the steps of: receiving environmental data (101) related to an area (400) to be sensed, preferably an area containing a luminaire (251), and optionally constraint data (102) related to the sensor network (200); identifying one or more suitable applications configured for using data (210) sensed by one or more of the plurality of sensors of the sensor network (200); determining at least one characteristic or optimized characteristic (302) of the sensor network (200) based on the environmental data (101), the identified one or more applications (301), and optionally on the constraint data (102).
2. 2. Method according to claim 1 , wherein the sensor network uses an existing luminaire network (250) or traffic light network.
3. 3. Method according to claim 2, wherein the area (400) to be sensed is an area containing a luminaire (251) of the luminaire network (250) or a traffic light of the traffic light network.
4. 4. Method according to any of the previous claims, wherein the identifying comprises selecting one or more suitable applications from a list of applications.
5. 5. Method according to any one of the previous claims, wherein the sensor network is an already existing sensor network comprising a plurality of already existing sensors and wherein environmental data comprises environmental data sensed by one or more of the plurality of already existing sensors.
6. 6. Method according to any of the previous claims, wherein the environmental data related to the area to be sensed comprises any one or more of: traffic data, such as vehicle/people counting data, ghost driver related data, traffic violation data, parking data, land use plans, air circulation data, noise maps, noise propagation maps, pollution data, weather data, crime data, data about one or more existing sensors if present in the area to be sensed, such as the position and/or type thereof, luminaire or traffic light data, such as position data and/or properties of a luminaire or traffic light if present in or in the vicinity of the area to be sensed, use type data, such a use as a terrace, a bicycle parking use, a (un)loading area use, etc., a user type data, such as use by children, animals, wheelchair users, elderly people, etc., objective related data related to environmental objectives for the area, such as less crime, less pollution, etc.
7. 7. Method according to any of the previous claims, wherein the method further comprises the step of receiving constraint data related to the sensor network and wherein the determining of the at least one characteristic or optimized characteristic of the sensor network is further based on said constraint data.
8. 8. Method according to any of the previous claims, wherein the constraint data comprises any one or more of: cost data related to the cost of the sensor network, sensor number data, such as a maximum or minimum number of sensors in the sensor network or a maximum or minimum number of different types of sensors in the sensor network, sensor type data, accuracy data, reliability data, sensor coverage data, sensor position data, such as preferred location data of a sensor to be added or to be relocated, a legal constraint such as a GDPR constraint or a no open source model constraint, application related data, such as a maximum or minimum number of applications to be used, resilience or weather condition related constraint data.
9. 9. Method according to any of the previous claims, wherein the at least one characteristic or optimized characteristic of the sensor network comprises the identified one or more suitable applications and any one or more of the following: one or more suitable sensor types to be used in the sensor network, one or more suitable combination of different sensor types to be used in the sensor network, one or more suitable sensor positions, one or more suitable orientations of a sensor of the sensor network, a number of sensors to be included in the sensor network, one or more suitable processing models configured to process data sensed by the sensor network.
10. 10. Method according to any one of the previous claims, wherein the determining of the at least one characteristic or optimized characteristic further comprises: selecting sensor types to be included in the sensor network from a list of available sensors, based on the one or more identified applications and on the environmental data and optionally on the constraint data; and/or determining suitable positions for said sensors based on the one or more identified applications and on the environmental data and optionally on the constraint data.
11. 11. Method according to any one of the previous claims, wherein the one or more suitable applications comprise any one or more of: an application related to the determining of traffic related data, such as a vehicle or pedestrian counting application, a ghost driver detection application, a traffic violation detection application; an application related to the determining of parking related data; an application related to the determining of air pollution data and/or sound pollution data and/or noise pollution data; an application related to the determining of crime related data; a use type detection application configured to detect one or more use types of said area, such as a curbside use, e.g. use as a terrace, a bicycle parking use, a (un)loading area use, etc.; a user type detection application configured to detect one or more user types in said area, such as a child, animal, wheelchair user, elderly people, etc.
12. 12. Method of any one of the previous claims, wherein application priority rules are used to determine which of the identified one or more suitable applications is to be used.
13. 13. Method of any one of the previous claims, wherein the identified at least one application uses one or more models, and wherein the method comprises configuring the one or more models based on sensed data.
14. 14. Method of the previous claim, wherein the one or more models comprise any one or more of the following: an object detection model, an object trajectory determining model, a model configured to determine if an object crosses a line, an object type determining model configured to determine a type of object.
15. 15. Method of claim 13 or 14, wherein the one or more models are pre-trained models and/or wherein the method comprises training the one or more models based on data sensed by the sensor network, wherein optionally the one or more models are one or more neural networks models.
16. 16. Method for commissioning of a sensor network, comprising the steps of: a. performing the method according to any of the previous claims; b. commissioning the sensor network based on the at least one determined characteristic or optimized characteristic of the sensor network.
17. 17. Method for optimizing a pre-existing sensor network comprising a. performing the method according to any of the claims 1-15 for optimizing the preexisting sensor network; b. modifying the pre-existing sensor network based on the at least one determined optimized characteristic of the sensor network and/or adding and/or removing one or more sensors to the pre-existing sensor network based on the determined optimized characteristic of the sensor network.
18. 18. A computer program comprising computer-executable instructions to perform the method, when the program is run on a computer, of any one of the previous claims.
19. 19. A digital data storage medium encoding a machine-executable program of instructions to perform any one of the steps of the method of any one of the claims 1-14.
20. 20. A computer program product comprising computer-executable instructions for performing the method of any one of the claims 1-14, when the program is run on a computer.

Description

METHOD FOR OPTIMIZATION OF SENSOR NETWORK PLACEMENT FIELD OF INVENTION The field of the invention relates to the field of sensor networks and more in particular, the determination and optimization of the placement of sensors in a sensor network. The field of the invention also relates to a computer system, platform or infrastructure therefor, as well as an edge device therefor. BACKGROUND Technological advancements in computing and telecommunication have drastically transformed the world. In particular, the growth of Internet of Things and cloud computing have been used to enhance the quality of services in cities. The integration of information, communication, and advanced sensors to manage city assets has lead to the concept of smart cities. In particular, sensor networks play a significant role in the collection of important information regarding the urban environment. Smart sensors are utilized in traffic control, curbside management, lighting, pollution control, garbage collection, energy management and monitoring, health, air quality, and food and water tracking such that smart cities improve sustainability and efficiency of various urban dynamics such as health, water, land, energy, etc. SUMMARY The amount of data that can be inferred from a sensor network and its use depends on multiple parameters, such as an amount of sensors that are present in the network, the position of the sensors, their environment, the types of sensors installed, etc. The installation of such a network of sensors also has a cost which may influence the choice of certain parameters. An object of embodiments of the invention is to provide a method that determines a sensor network to be installed and/or optimizes an already existing sensor network. According to a first aspect of the invention, there is provided a method for installing and/or optimizing a sensor network comprising a plurality of sensors. Preferably, an existing luminaire network or traffic light network may be used for the installing and/or optimizing. The method comprises the steps of receiving environmental data related to an area to be sensed. Optionally, the method also comprises receiving constraint data related to the sensor network. The method comprises the steps of identifying one or more suitable applications configured for using data sensed by one or more of the plurality of sensors of the sensor network and of determining at least one characteristic or optimized characteristic of the sensor network based on the environmental data, the identified one or more applications and optionally on the optional constraint data. Preferably, the area includes a luminaire or a traffic light. In other words, in exemplary embodiments the method may optimize a sensor network by using data sensed by the sensor network to identify one or more applications that are capable of using the sensed data in a meaningful way. The method also optimizes the sensor network by determining at least one characteristic of the sensor network, e.g. the position of sensors to be installed and/or optimized, their orientation, the amount thereof. This determination is based on environmental data related to the area to be sensed. Optionally, additional data in the form of constraint data may be used for the determination. In this way, a sensor network that better corresponds to the area to be sensed is obtained. The sensor network may not be installed yet. For example, city planners or the police may be interested in installing a sensor network in a given area, which does not comprise any sensor yet. Alternatively, the sensor network may be an already existing network, e.g., a sensor network that needs to be optimized, improved, or replaced. For example, the area to be sensed, which may or may not comprise the sensor network may comprise several sub-areas, with among them a first well illuminated and busy commercial area, with streets filled with traffic and parking spaces, a second calm and dark residential area which is safe and a third dark residential area where several crimes, e.g., burglaries, thefts or graffiti’s, have happened in the last years. In that situation, the method may identify applications for the first area such as a traffic monitoring application and a parking monitoring application, due to the presence of the road and the parking spaces thereof. The method may also identify an air quality and/or noise monitoring application in the first commercial area, since heavy traffic may induce a high level of noise and air pollution. A crime monitoring application may also be expected to be identified in the third residential area. The method may also determine, based on the environmental data and on the identified applications, that to install and/or optimize the sensor network, it may be interesting to install, add and/or replace some visible light cameras in the commercial area, e.g. install and/or add several cameras pointing at the road crossings to better monitor the traf