A method and device for managing systems of a facility

Abstract

A method is disclosed. The method is performed by an electronic device for managing systems of a facility. The method comprises receiving a first set of data comprising first data associated with the facility. The method comprises receiving a second set of data comprising second data associated with at least one person with access rights for the facility. The method comprises receiving third data indicative of an occupancy rate for at least one portion of the facility. The method comprises modifying, based on the second data and / or third data, the first data.

Description

[0001] A METHOD AND DEVICE FOR MANAGING SYSTEMS OF A FACILITY

[0002] The present disclosure relates to a method for managing systems of a facility, and a related device for the same.

[0003] BACKGROUND

[0004] Managing facilities to effectively and efficiently use office space has become increasingly challenging due to increasingly common remote and hybrid working arrangements. The years following the Covid 19 pandemic have seen more under- and unutilized office space as the expectations or obligations for workers’ physical presences at their office has changed. While workers may have been present nearly all the time in the pre-Covid19 times, the spectrum now spans from zero to 100-percent office attendance. This has impacted the way company resources, including facilities, are managed, and it has created unrealized opportunities for flexibility, resources savings, and information transfer.

[0005] SUMMARY

[0006] Facilities occupancy and utilization impact the experience and performance, including the productivity, such as the efficiency and / or efficacy, of organizational resources. Static office attendance mandates, for example, may not account for positive and negative effects on resource utilization, or people, and they may be over- or under-inclusive.

[0007] Recognizing, accounting for, and managing impacts of occupancy of or physical attendance at company facilities may increase the effective, such as efficient and / or efficacious, utilization of facility resources to increase enterprise productivity. In other words, a policy that supports both efficacy and efficacy may be based on objectively collected data to achieve desired outcomes of allocating an appropriate number of resources to accomplish company objectives while maintaining engaged employees.

[0008] Accordingly, there is a need for devices and methods for managing systems of a facility, which mitigate, alleviate or address the shortcomings existing and provide resource management, including managing and / or modifying attendance policies to support effective, such as efficient and / or efficacious, facilities and resource occupancy and utilization.A method for managing systems of a facility is provided. The method is performed by an electronic device, such as a device or devices. The method comprises receiving a first set of data comprising first data associated with the facility. The method comprises receiving a second set of data comprising second data associated with at least one person with access rights for the facility. The method comprises receiving third data indicative of an occupancy rate for at least one portion of the facility. The method comprises modifying, based on the second data and / or third data, the first data.

[0009] Further, a first electronic device for managing systems of a facility is provided. The first electronic device comprises memory circuitry and processor circuitry. The first electronic device is configured to receive a first set of data comprising first data associated with the facility. The first electronic device is configured to receive a second set of data comprising second data associated with at least one person with access rights for the facility. The first electronic device is configured to receive third data indicative of an occupancy rate for at least one portion of the facility. The first electronic device is configured to modify, based on the second data and / or third data, the first data.

[0010] It is an advantage of the present disclosure that facilities may be managed based on analyses of data representative of usage of a facility, which in turn may be a result of a policy governing usage of the facility.

[0011] Further, it is an advantage of the present disclosure that policies governing access to a facility may be evaluated and / or modified based on data received from electronic devices associated with people, such as employees, operating according to the policy. The disclosed method and electronic device (such as the first electronic device) may for example enable an improved adaptability and / or flexibility of the resource utilization at the facility, such as by modifying the first data.

[0012] It is a further advantage of the present disclosure that business and / or policy objectives may be represented as technical data, and such data may be evaluated and modified using machine learning and / or artificial intelligence techniques on time scales not achievable by human effort.

[0013] Further, it is an advantage of the present disclosure that data from electronic devices communicating with one another may be captured and analyzed to support facilitiesmanagement and associated policy changes tailored to specific inputs, such as specific employees.

[0014] It is a further advantage of the present disclosure that an electronic device associated with one or more systems of a facility may be controlled by another electronic device associated with the one or more systems, for example in support of an employee attendance policy, based on data gathered by the system.

[0015] Further, the method and electronic device disclosed herein may advantageously enable a reduction in the carbon footprint associated with the facility, namely by optimizing the resource utilization, such as by updating one or more attendance parameters associated with an attendance policy.

[0016] It is a further advantage of the present disclosure that resources may be effectively allocated, utilized, and our scheduled to support energy use, reduce emissions, effectively use office space, efficiently schedule and / or use manufacturing equipment, manage data processing and transfer, support water and waste management, and enable effective use by employees of office space, such as through meeting efficacy and / or efficiency.

[0017] BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and other features and advantages of the present disclosure will become readily apparent to those skilled in the art by the following detailed description of example embodiments thereof with reference to the attached drawings, in which:

[0019] Fig. 1 is a diagram illustrating an example system for managing systems of a facility comprising example electronic devices of the facility according to this disclosure, Figs. 2A-2B show a flow-chart illustrating an example method, performed by an electronic device, for managing systems of a facility according to this disclosure, and

[0020] Fig. 3 is a block diagram illustrating an electronic device for managing systems of a facility according to this disclosure.

[0021] DETAILED DESCRIPTION

[0022] Various example embodiments and details are described hereinafter, with reference to the figures when relevant. It should be noted that the figures may or may not be drawn toscale and that elements of similar structures or functions are represented by like reference numerals throughout the figures. It should also be noted that the figures are only intended to facilitate the description of the embodiments. They are not intended as an exhaustive description of the disclosure or as a limitation on the scope of the disclosure. In addition, an illustrated embodiment needs not have all the aspects or advantages shown. An aspect or an advantage described in conjunction with a particular embodiment is not necessarily limited to that embodiment and can be practiced in any other embodiments even if not so illustrated, or if not so explicitly described.

[0023] A company may establish a policy governing or mandating how many days a particular employee should be physically present in their designated work location, such as their office. This may present challenges for enforcement and, further, may be present challenges to facilities managers in understanding how such a policy affects resource allocation and / or returns on investment in the facility. Such policies may also present challenges because their efficiency and / or efficacy may be unevaluated. In other words, a strict requirement that employees physically attend an office without further assessment and analysis of technical data associated with such attendance may result in an inefficient utilization of resources; or such policies may be efficient but not necessarily efficacious in that they may not accomplish their objectives. This could be in the form of unnecessary costs or encouraging unnecessary carbon emissions. The inverse is also possible: a policy that does not adequately account for resource utilization may cause strains on facilities systems and resources if they are not appropriately sized for the demand.

[0024] Further, such policies may result in increased carbon emissions and / or footprints associated with the facility, such as caused by employees commuting to and from the facility. Additionally or alternatively, such policies may not be updated based on objective data that indicates whether the policy’s goals are actually achieved.

[0025] Working environments, however, may provide data that can be autonomously harvested and evaluated in manner not previously considered or previously available. As disclosed herein, systems and devices associated with a facility may be configured to capture usage related to productivity and / or attendance at a facility. Such systems may determine effectiveness, efficacy, and / or costs of various efforts, including polices, and implement changes to facilities and resources of a facility may be managed accordingly.An attendance policy may affect company and / or employee performance toward specific goals or targets. An attendance policy may support company efforts to mitigate contributions to climate change, for example, by supporting efforts to identify and track impacts of the policy on carbon emissions. Additionally or alternatively, an attendance policy may be tailored with transportation (such as public transportation, ridesharing, and / or bicycle) subsidies or the like to support such goals. An attendance policy may support specific employees by prompting working arrangements that promote career growth, team participation, and organizational engagement. Broad or static attendance policies may be unable to account for changes or specific employee, organizational, or team considerations. As disclosed herein, however, dynamic, automated, and data-based decision-making for policies may yield better results. Such a dynamic policy may also be tailored to accomplish certain objectives related to efficacious use of facilities that promote both employee engagement and productivity.

[0026] By way of example, data related to utilization of a facility, such as based on the manner in which electronic devices (and the device users) communicate within the facility, may be analyzed for management of facility and / or resources of the facility. Such data may be, for example, representative of an attendance policy. Data captured may be anonymous, anonymized, and / or aggregated to protect individual privacy and to support operations that provide for effective resource management while encouraging user engagement and well-being. Modifications to the data by the system may allow for implementations of the attendance policy that support such organizational objectives. Such modifications may be tailored to individual employees to improve benefits of in-person or remote work to improve visibility and growth. Further, such modifications may be seen as de-risking decisions by providing input and suggested or actual changes based on implementation, which may mitigate negative impacts or improve or reiterate positive impacts. The technical solutions described herein may thus provide allow for improved allocation of company resources and individual decision making based on such resource allocation.

[0027] The figures are schematic and simplified for clarity, and they merely show details which aid understanding the disclosure, while other details have been left out. Throughout, the same reference numerals are used for identical or corresponding parts.

[0028] Fig. 1 is a diagram illustrating an example system 1 for managing systems of a facility, including resources of facility, comprising an example electronic device 300, an exampleelectronic device 400, and, in one or more examples, other electronic devices 400A and / or 400B, according to this disclosure. In one or more examples, electronic device 300 is seen as a first electronic device and electronic device 400 is seen as a second electronic device according to this disclosure. In some examples, the electronic devices 400A and 400B may be seen as second and third electronic devices according to this disclosure. The electronic device as disclosed herein, such as electronic device 300, may be referred to as a first electronic device.

[0029] The electronic devices 300, 400, 400A, and 400B may be configured to communicate with one another via wired or a wireless links (or radio access links) 10, 10A, 10B. The electronic devices 300400, 400A, and 400B may communicate with one another, either directly or via another electronic device (such as electronic device 400 communicating with electronic device 400A via electronic device 300). The links 10, 10A, 10B may represent communications via a wireless local area network (WLAN), such as WiFi, cellular communications, for example, via a 3GPP wireless communication system, Bluetooth communications, or other wireless communications, such as Zigbee, RFID, or NFC. In one or more examples, links 10, 10A, 10B represent wired communication via, for example, USB, HDMI, coaxial cable, fiber optics, or another physical connection.

[0030] The electronic devices 300, 400, 400A, and / or 400B may each be a mobile device, wearable electronic device, or sensor, or any combination thereof. In one or more examples, the electronic devices 300, 400, 400A, and / or 400B may be a mobile phone, a tablet, a wearable device (such as a smart watch or location tracker), an identification fob, or an access card.

[0031] In one or more examples, electronic devices 400, 400A, and / or 400B may be configured to detect and / or collect data from (or as a condition of) a person entering a building. Such devices may include biometric detection devices, such as devices configured for image recognition, facial detection, fingerprint recognition, retinal scanning, thermal scanning or the like. Devices 400, 400A, and / or 400B may be configured as such devices or may work in conjunction with such devices and may communicate data collected by such methods to one another and / or electronic device 400.

[0032] Electronic device 300 may, in one or more examples, be a server, such as a cloud-based server, controller, control console, control panel, or central scheduler. Electronic device300 may be a mobile phone, a tablet, a wearable device (such as a smart watch or location tracker), an identification fob, or an access card, which may have different user or supervisory priorities or privileges than, for example, electronic device 400. Electronic device 300 may be understood as a control node.

[0033] In one or more examples, system 1 is configured to manage a facility, which may include various resources. System 1 may be configured to manage, such as monitor and update, a policy or policies governing use of, such as occupancy and / or attendance at, a facility or facilities. Electronic device 300 may be a control node configured to manage an office attendance policy (such as obligations for employee attendance) and other resources. Electronic device 300 may manage resources of a facility, which may include office attendance, in real-time and / or without intervention from a user. System 1 may support occupancy tracking for a facility. Data from sensors within such a facility may be obtained by and stored in memory or storage circuitry of electronic device 300. For example, sensors within a facility may collect data related to an electronic device 400 associated with an occupant of or attendee at a facility, such as an employee or contractor, and may transmit such data to electronic device 300.

[0034] In one or more examples, an electronic device 400 may be configured to detect, for example, infrared (IR) radiation or energy associated with a person or people entering a facility, such as building. In such an example, electronic device 400 may capture data related to occupancy and report such data, which may be anonymous. In other words, such data may indicate that a person or people have passed a give point, such as a location of electronic device 400, but such data may not be identifying of a particular person. In such cases, an overall occupancy of a building may be determined, and the identity of any one person may be protected (or otherwise unknown or undetected).

[0035] The data described herein, such as the first, second, third, and / or fourth data, may comprise, such as may include an electronic representation of, the various policies, parameters, and criteria described herein.

[0036] Electronic device 300 may be configured to receive, such as from electronic device 400 via link 10, a first set of data comprising first data associated with a facility, such as a facility managed by system 1. Electronic device 300 may be configured to receive, such as from electronic device 400A via link 10A, a second set of data comprising second dataassociated with at least one person with access rights for the facility. Access rights may be seen as permission to enter and remain at a facility, such as a portion of a facility, such as a building and / or office. In other words, a person with access rights may be seen as being able to access the facility. A person with access rights for the facility may for example be an employee at the facility.

[0037] Electronic device 300 may be configured to receive, such as from electronic device 400B via link 10B, third data indicative of an occupancy rate for at least one portion of the facility. Electronic device 300 may be configured to modify, such as with processing circuitry 302, based on the second data and / or third data, the first data.

[0038] As used herein, modifying the first data, such as modifying an attendance policy or aspect of an attendance policy, may be seen as suggesting a modification, which may include an indication and / or analysis of the rationale for such a modification and / or the benefits or challenges (for example, pros and cons) of such a modification. Electronic device 300, and / or system 1 as a whole, may thus be configured to provide, for example, guidance or recommendations based on the second data and / or third data, for modifying the first data. In one or more examples, such suggestions, which may be seen as recommendations, guidance, and / or options, and may involve further action, such as user input, such as approval and / or acceptance, before such modifications are implemented. In such examples, electronic device 300 may be configured to identify some or all of the aspects of the second data and / or third data supporting such a recommendation; or electronic device 300 may be configured to analyze, such as with ML model 12, the second and / or third data and provide metrics that support the suggestions, which metrics may or may not be extracted directly from the second data and / or third data. Accordingly, anonymity of such data may be preserved.

[0039] An occupancy rate can for example be seen as a rate associated with an occupancy (such as of persons with access rights) at the facility. For example, the occupancy rate may comprise a ratio of used space to total space of a facility, such as a portion of a facility, such as a building, office, manufacturing area, warehouse, laboratory, and / or collection of working space. In one or more examples, the occupancy rate may be or may include an attendance rate. An attendance rate may be seen as a quantity and / or rate at which people associated with the facility (such as employees and / or contractors) areattending (such working at) the facility. An attendance rate may be a ratio of anticipated to actual employee attendance.

[0040] In one or more examples, the first data comprises one or more attendance parameters associated with an attendance policy. In other words, the first data may comprise one or more parameters (for example, attendance parameters) associated with an attendance policy for at least one person with access rights for the facility. An attendance policy (which may also be referred to as an office attendance policy) may be seen as a formal set of guidelines, such as written guidelines, which may be in electronic form, that set forth employee expectations related to physical presence at their workplace. The attendance policy may include one or more attendance parameters, which may be seen as specific requirements or expectations. In one or more examples, the attendance policy may be determined based on the one or more attendance parameters.

[0041] Attendance parameters may include, for example, regular working hours, which may be or include times of day employees should arrive, leave, and / or be available during the workday. Attendance parameters may include work location requirements, which may include whether employees must work on-site, remotely, or in a hybrid arrangement combining both on-site and remote work. For example, the attendance parameters may comprise information indicative of a number of days that an employee must work on site, such as at the facility. Attendance parameters may include allowances for flexible scheduling, including arrival times or compressed workweeks. Attendance parameters may include notification procedures, such as how employees should communicate absences, late arrivals, or schedule changes. Attendance parameters may include time tracking methods, which may be associated with a system, such as employee time reporting system, which may be seen as a hardware and / or software system used to record and verify employee attendance. Attendance parameters may include leave policies, such as the manner in which vacation, sick days, and other types of leave integrate with attendance expectations. Attendance parameters may include compliance consequences, which may specify what happens if employees fail to adhere to attendance requirements. The attendance policy may for example be seen as being characterised by one or more attendance parameters.

[0042] In one or more examples, the first data comprise one or more historical attendance parameters, such as one or more attendance parameters associated with an historicalattendance record and / or an historical version (such as a past version or indicator) of any of the foregoing attendance parameters.

[0043] In one or more examples, the first data comprise a calendar day parameter, such as a parameter associated with designated calendar days. An office attendance policy as described herein may include designated calendar days associated with one or more attendance parameters.

[0044] In one or more examples, data (such as the second and / or third data) received from an electronic device 400 may include or be indicative of a turnover parameter. Additionally or alternatively, an attendance policy may have a turnover parameter. A turnover parameter may be seen as a value related to or indicative of, such as a target, for a quantity of employees whose employment is terminated. A turnover parameter may, for example, be indicative of employee turnover based on a work location, such as in-person or remote. In one or more examples, a turnover parameter may be expressed as a ratio of turnover of in-person and / or hybrid employees to turnover of remote employees.

[0045] An attendance policy may have different attendance parameters associated with different employees and / or different classifications of employees. In one or more examples, the first set of data comprises first data representative of a title, a role within the facility, a security clearance, a seniority level, an employment status, an immigration or citizenship status, a job code, a job function, a professional credential, an identification, an ability, a location, a time zone, a telephone number, or any combination thereof. For example, the first data may be associated with and / or may affect one or more attendance parameters. In one or more examples, an attendance policy and / or an attendance parameter may indicate how long a particular employee, or a number of employees, has been in a position within a company. In one or more examples, an attendance policy and / or an attendance parameter may indicate and / or may be based on career progress, such as tracking career progress for one or more employees. In one or more examples, the first set of data comprises first data obtained from, such as exported from, an employee time reporting system.

[0046] In one or more examples, modifying an attendance policy includes suggesting modifications which may be implemented provisionally or not implemented without further approval. In one or more examples, a modification or suggested modification comprises auser-specific or employee-specific recommendation to be approved or updated (for example, opted into) by one or more users. In one or more examples, a modification or suggestion comprises a generalized recommendation for more than one user, such as a recommendation for a group. Such recommendations may be made, for example distributed to and / or communicated with users, without further input, in some examples. In other words, in various examples, modifications may be fully or partially automated; in some examples, an attendance policy may be modified, such as changed, substantively without further input; in some examples, an attendance policy may be modified by making recommendations for substantive modification, such as substantive change. Changes to company-wide policy parameters, for example, may be made without further input; changes to employee-specific policy parameters may be made contingent to further input.

[0047] In one or more examples, modifications may include changes to operations, resource allocation, expectations of certain employees, or the like. Modifying a policy must thus be seen as a modification to, for example, a written policy, which may then be implemented or executed. Or as described herein, modifying a policy may include substantive changes that implemented, such as implemented within certain targets or limits, such as financial targets or limits governed by other policies, laws, or regulations.

[0048] Electronic device 300 may be configured to modify the first data by generating fourth data, such as by applying a machine learning (ML) model 12 to the second data and / or third data. In one or more examples, ML model 12 is applied to the first data, the second data, and / or the third data. ML model 12 may comprise an additive regression model and / or a temporal fusion transformer. The fourth data may thus comprise a modified version of the first data.

[0049] As used herein, an ML model, such as ML model 12, may be understood to be or to comprise a computational algorithm. An ML model may map input data to desired outputs, which may include identifying statistical patterns, such as through an iterative process of training. Training an ML model may be referred to as learning. An ML model may include parameters, such as numerical values, which in turn may be numbers representing weights and biases. Parameters of an ML model may represent parameters of other data sets. For example, a parameter of an ML model may represent an aspect of a company policy. In one or more examples, each attendance parameter, turnover parameter, and / or other policy parameter described herein is represented by a parameter of ML model 12.A parameter of an ML model may be adjusted during training, such as through learning. Such adjustments may be made to decrease, such as minimize, the difference between the model's predictions and the actual preferred outputs, which may be seen as correct outputs. An ML model may be a configuration of computational units that define how input data is processed and transformed. An ML model may be understood to operate like neurons in a biological system. An ML model may be, or may be referred to as, a neural network.

[0050] According to the present disclosure, a processor, such as processor circuitry 302, may comprise ML model 12 and / or may read data and / or other indication(s) of ML model 12 from memory. ML model 12 may reside in memory and / or processor circuity 302. Thus, electronic device 300 may be understood as comprising ML model 12 when, for example, electronic device 300 that is powered off.

[0051] Application or use of neural networks and / or ML models differs from other programming or software implementations because the model may not follow pre-defined rules; rather, the ML model may have decision-making (for example, inference) logic created from or based on the patterns present in training data and learned during the training process.

[0052] Training an ML model (or neural network) may be understood as a process or procedure that systematically updates the ML model parameters. This may include mathematical and / or statistical analysis of errors between predicted and actual or desired results.

[0053] In one or more examples, ML model 12 comprises an additive regression model, which may be seen as a statistical model that expresses an outcome variable, such as output data, as the sum of multiple predictor functions, such as input data, each representing a different input variable.

[0054] In one or more examples, ML model 12 comprises a temporal fusion transformer, which may be seen as a neural network designed for time series forecasting. A temporal fusion transformer may combine attention mechanisms with specific components for handling time-based data. Attention mechanisms may be seen as components in neural networks that help the model, such as ML model 12, focus on relevant parts of the input data to reach on inference. ML model 12 may thus use attention mechanisms to weigh the importance of different time steps and variables, such as attendance parameters, toproducing predictions for multiple future time points about the appropriateness of an attendance policy.

[0055] In one or more examples, ML model 12 may be or may comprise a different model, such as a supervised learning model, a time series model, a probabilistic model, and / or a model employing dimensionality reduction.

[0056] Accordingly, electronic device 300 may be configured to select, such as automatically select or identify, one or more aspects of the first set of data, the second set of data, and / or the third set of data and provide interpretable results, such as fourth data, such as while handling missing data and / or mixed frequencies in the input. By contrast to an individual, such as a person, manually updating an attendance policy, ML model 12, and thus electronic device 300 and system 1, may receive and analyze complex time patterns, determine salient data, and make multiple concurrent inferences to update the attendance policy and / or otherwise manage resources of a facility.

[0057] In one or more examples, the second set of data (such as the second data) comprises a productivity parameter associated with a productivity of one or more persons and / or organizations associated with the facility. Accordingly, electronic device 300 may be configured to modify the first data based, for example based in part, on the productivity parameter, such as whether a criterion associated with the productive parameter is met.

[0058] A productivity parameter may be based on quantitative metrics, such as time efficiency, which may be a difference between an actual duration for completion of a task or event and a planned or scheduled duration of such task or event. In one or more examples, a productivity parameter may include a completion rate, which may be a percentage of predefined tasks or items completed. A productivity parameter may include a decisionmaking rate, which may be a quantity of actionable decisions made during an event, a workday, and / or in a set time period. In one or more examples, a productivity parameter may include costs associated with certain operations or efforts, which may include, for example, a value of wages divided by outcomes. A productivity parameter may thus be a measure of how productive, or not, one or more employees are depending on whether they use office resources, work remotely, commute, commute certain distances, or the like. In one or more examples, a productivity parameter be a measure of how productive, or not, a group of employees, such as a team or function, or a category of employees,such as a particular job code, is depending on whether and how they work, such as inoffice or remotely, whether or how they commute, or the like.

[0059] Additionally or alternatively, a productivity parameter may be based on and / or an indicator of efficacy of, for example, an attendance policy. A productivity parameter may include an indication or data representative adherence to certain criteria, such as performance indicators and / or team values (such as enumerated corporate values, such as objectively measurable values or indicators). A productivity parameter may indicate how certain events, populations, or combinations of people working at a certain location achieve, or not, an objective.

[0060] In one or more examples, a productivity parameter is based on objective data or information (such as objective measures) captured for in-person and / or virtual attendance; it may include data from audio-visual or online meeting tools. Such objective measures may include speaking time distribution among participants, patterns of interaction among participants, frequency of interruptions, and / or perceived engagement levels, such as based on comments or chat app usage.

[0061] In one or more examples, a productivity parameter is based on analysis, such as a semantic analysis, of data collected during an event or during work on a task. Such data may include minutes of meeting, a transcription, and / or audio recording, which may have, for example, documentation of actions assigned, decisions made, and / or adherence to agenda or schedule. A productivity parameter may reflect an extent of participation by one or more participants. The basis for a productivity parameter may be a function of a work and / or employee type; for example, a productivity parameter may be an indicator of participation in certain work or execution of tasks.

[0062] In or more examples, a productivity parameter may be based on, such as additionally based on, a time of day, a day of the week, and / or a day of the month. For example, a productivity parameter may be affected by, for example, environmental conditions, such as temperature and / or light, a percentage of team members physically present and remote, or the like.

[0063] In one or more examples, a user, such as an employee, may elect to share certain data and / or to engage with an attendance policy, such as via electronic device 300. Such datamay be or may include staff and / or employee survey data, exit interview data, employee and / or supervisor interview data, overtime data, timekeeping for fees, annual leave data, sick leave data, or the like. Such a user may provide permission for data, such as personal identifying information, to be used or accessed. A permission indicator may be seen as such permission. In one or more examples, the second data set comprises a permission indicator, such as a permission indicator for logging access to at least one resource of a facility and / or for using data to determine or identify a productivity parameter.

[0064] As used herein, a criterion may be a target or measure by which to evaluate the appropriateness of a parameter. For example, if a criterion, which may be a threshold (such as a numerical value), is met with certain frequency, that may suggest, and ML model 12 may determine, that a parameter should or should not be changed, subject to the learnings of ML model 12.

[0065] In one or more examples, electronic device 300 may be configured to determine at least one resource associated with the facility. The first set of data may comprise data associated with the at least one resource.

[0066] A resource, such as a resource of a facility, may be seen as one or more elements that may be relevant to and potentially available for or within a facility. A resource may be an interior location (such as internal to a facility, such as a building) or an exterior location (such as external to a facility, such as a building). A resource may be a building. In one or more examples, a resource may include equipment for the meeting, such as audio-visual equipment or accessibility equipment to make a meeting more accessible for those with special needs, such as visual and / or audio impairment, such as limited mobility. In one or more examples, a resource may include catering or other hospitality-related options, for example, snacks, meals, or beverages for an event. In one or more examples, a resource may include a database (such a list or file) of participants of an event, including potential participants. In one or more examples, a resource may include one or more of a designated portion of the facility, a room, a portion of a room, an exterior location, office equipment, laboratory equipment, audio / visual equipment, food service equipment, collaboration tools, exercise equipment, machinery, an accessibility tool, or a vehicle. Such resources may be seen as a set of resources, which include one or some or all such resources.In one or more examples, a resource, such as office equipment, is identifiable by a unique identifier, such as an IP address, a MAC address, and / or an IMEI, which may be associated with a company and / or an employee of the company.

[0067] In one or more examples, the first set of data comprises data associated with at least one resource, which comprises a quantity of workstations, a quantity of seats, a designated location of one or more employees, or a quantity of employees, or any combination thereof.

[0068] Electronic device 300 may be configured to receive, such as receive directly without input from another electronic device 400, the first data via a user interface, such as user interface 304. In one or more examples, user interface 304 comprises a user chat interface, which may be or may be connected with a dashboard that is accessible by one or more users.

[0069] Additionally or alternatively, electronic device 300 may be configured to receive the second data from electronic device 400A, which may be associated with the at least one person with access rights to the facility and / or from electronic device 400B, which may be associated with another person with different access rights. As used herein, different access rights may be based on or associated with different attendance parameters. In one or more examples, different access rights are seen as different permissions to enter the facility, such as a portion of the facility, such as a building and / or office, or to use different resources. In one or more examples, an employee who, according to an attendance policy, is expected to work in an office has different access rights than another employee expected to work remotely.

[0070] In one or more examples, electronic device 300 may be configured to receive the second data from (for example, electronic device 400A and / or 400B may comprise) at least one of an occupancy sensor, a card reader, a fob reader, an access point, a keypad, a network node, a wireless router, a server, a camera, a biometric identifier, a facial recognition system, a quick response, QR, code reader, a proximity sensor, a wearable electronic device, a mobile phone, a tablet, or a computer, or any combination thereof.

[0071] Electronic device 300 may be configured to operate according to logic and / or controls for managing access to a facility and / or to resources of the facility. Electronic device 300 mayinclude logic and / or controls for managing environmental conditions, such as mechanical (such as heating, ventilation, and cooling (HVAC), plumbing, humidity, scents (such as perfumes or air fresheners)), electrical (such as power, communications, audio-visual, sound (such as ambient sound or music)), and / or life safety (such as fire alarm, security, emergency back-up) of a facility. Electronic device 300 may thus be integrated with other systems or subsystems of the system 1, including, for example, mechanical, electrical, and / or life safety.

[0072] In one or more examples, electronic device 300 is configured to, such as with processing circuitry 302, determine based on the modified first data, control data for controlling an electronic device 400B, which may be a third electronic device. For example, electronic device 400B may be an aspect of on the systems or subsystems described in the foregoing. Electronic device 300 may thus be configured to control, based on the control data, electronic device 400B. Control, as used herein, may be seen as managing the various operations of the system or subsystem of which electronic device 400B is a part.

[0073] Figs. 2A-2B show a flow diagram of an example method 100 performed by an electronic device according to the disclosure, for managing systems of a facility. The electronic device is the electronic device (such as the first electronic device) disclosed herein, such as the electronic device 300 of Figs. 1 and 3.

[0074] In one or more examples, the method 100 comprises determining S101 at least one resource associated with the facility.

[0075] In one or more examples, the first set of data comprises data associated with the at least one resource.

[0076] In one or more examples, the at least one resource comprises a unique identifier indicative of the at least one resource.

[0077] In one or more examples, the at least one resource comprises at least one of a designated portion of the facility, a room, a portion of a room, office equipment, laboratory equipment, audio / visual equipment, food service equipment, collaboration tools, exercise equipment, machinery, an accessibility tool, or a vehicle, or any combination thereof.In one or more examples, the at least one resource comprises a wireless local area network (WLAN) associated with the facility. Additionally or alternatively, the at least one resource comprises a Bluetooth connection, a Zigbee connection, an RFID connection, or an NFC connection, or any combination thereof. The at least one resource may be seen as a connection supporting wireless or radio communication.

[0078] The method 100 comprises receiving S102 a first set of data comprising first data associated with the facility.

[0079] In one or more examples, the first data comprise one or more attendance parameters, such as one or more attendance parameters associated with an attendance policy.

[0080] In one or more examples, the first data comprise one or more historical attendance parameters, such as one or more historical attendance parameters associated with an historical attendance record.

[0081] In one or more examples, the first data comprise a calendar day parameter, such as a calendar day parameter associated with one or more designated calendar days.

[0082] In one or more examples, the first data is received from an external device via the Internet.

[0083] In one or more examples, the method 100 comprises receiving S102A the first data via a user interface of the first electronic device.

[0084] In one or more examples, the first set of data comprises first data exported from an employee time reporting system.

[0085] In one or more examples, the first set of data comprises data associated with at least one of a quantity of workstations, a quantity of seats, a designated location of one or more employees, or a quantity of employees, or any combination thereof.

[0086] In one or more examples, the first set of data comprises data representative of a title, a role within the facility, a security clearance, a seniority level, an employment status, an immigration or citizenship status, a job code, a job function, a professional credential, an identification, an ability, a location, a time zone, a telephone number, or any combination thereof.In one or more examples, the first set of data comprises data representative of traffic, weather, employees, and / or an organization of the person with access rights for the facility. An organization of a person may be seen as a team, business unit, corporate division, shift, or similar group of which the person is a part and / or a member.

[0087] In one or more examples, the first set of data comprises one or more parameters, such as a criterion or criteria, associated with an attendance policy. The criterion may be for example based on a threshold at, above, or below which a decision may be made or suggested.

[0088] The method 100 comprises receiving S104 a second set of data comprising second data associated with at least one person with access rights for the facility.

[0089] In one or more examples, the second data comprise data exported from another system associated with the facility.

[0090] In one or more examples, the second data is exported from the employee time reporting system.

[0091] In one or more examples, the second data comprise data representative of address information, such as address information for the at least one person with access rights for the facility.

[0092] In one or more examples, the second data comprise data representative of a transportation mode.

[0093] In one or more examples, the second data comprise data representative of a commuting route, such as for the at least one person with access rights for the facility. A commuting route may be seen as a route, such as a transportation route or path, between the at least one person’s residence and their place of work, such as their office. The place of work may be a location designated in, for example, an attendance policy.

[0094] In one or more examples, the second data comprise updated second data. Updated second data may be seen as a derivative of or variation of the second data.

[0095] In one or more examples, the second data comprise data received from a second electronic device (for example a second set of data received from a second electronicdevice) that comprises at least one of an occupancy sensor, a card reader, a fob reader, an access point, a keypad, a network node, a wireless router, a server, a camera, a biometric identifier, a facial recognition system, a quick response, QR, code reader, a proximity sensor, a wearable electronic device, a mobile phone, a tablet, or a computer, or any combination thereof.

[0096] In one or more examples, the second set of data comprises a permission indicator for logging access to at least one resource of the facility.

[0097] In one or more examples, the second set of data comprises data representative of at least one of a survey, an exit interview, timekeeping, or payroll, or any combination thereof.

[0098] In one or more examples, the second set of data comprises data associated with at least one other person, such as with different access rights to the facility.

[0099] In one or more examples, the second set of data comprises data representative of a title and / or a job code, for example, a title and / or job code of one or more people with access rights, such as different access rights, to the facility. A job code may be seen as, for example, an alphanumeric identifier of a particular job, role, or function within a company. A title may be seen as a descriptive identifier of a particular job, role, or function within a company.

[0100] In one or more examples, the second set of data comprises data representative of a commuting distance, a transportation mode, and / or a traffic condition. A transportation mode may be seen as a type of transportation, such as automobile, locomotive (such as a train), subway (such as metro), tram, bicycle, scooter, and / or pedestrian means. A traffic condition may be seen as conditions on a roadway and / or other means of communication that affect movement, such as vehicle traffic.

[0101] In one or more examples, the second set of data comprises data representative of traffic, weather, employees, and / or an organization of the person with access rights for the facility. Traffic may be seen as a traffic condition and / or a quantity of vehicles and / or people affecting a traffic condition.In one or more examples, the second set of data comprises data representative of a commuting distance for at least one person, such as the at least one person with access rights for the facility and / or another person associated with the facility.

[0102] In one or more examples, the method 100 comprises receiving S104Athe second data, such as receiving the second set of data, from a third electronic device associated with at least one person, such as the at least one person with access rights to the facility and / or with another person with different access rights.

[0103] In one or more examples, the second set of data comprises a productivity parameter associated, such as a productivity parameter associated with a productivity of one or more persons and / or organizations associated with the facility.

[0104] The method 100 comprises receiving S106 third data indicative of an occupancy rate for at least one portion of the facility.

[0105] In one or more examples, the third data comprise updated third data.

[0106] In one or more examples, the third data is based on access to the WLAN. Additionally or alternatively, the third data is based on access to the Bluetooth connection, the Zigbee connection, the RFID connection, or the NFC connection, or any combination thereof.

[0107] In one or more examples, the method 100 comprises determining S110 a turnover parameter associated with employee turnover, such as based on the second data and / or the third data.

[0108] In one or more examples, the method 100 comprises determining S112 an emission parameter, such as an emission parameter associated with carbon dioxide emissions, such as based on the second data and / or the third data. Carbon dioxide emissions, which may also be referred to as carbon emissions, may be seen as quantifiable emissions of carbon dioxide, such as from a transportation mode, that may contribute to, or be perceived to contribute to, anthropogenic climate change.

[0109] In one or more examples, the method 100 comprises obtaining S114, such as determining, such as based on the first data, the second data, and / or the third data, acommuting parameter, such as a commuting parameter associated with a commuting cost for the at least one person with access rights for the facility.

[0110] In one or more examples, the method 100 comprises obtaining S116, such as determining, such as based on the first data, the second data, and / or the third data, a metric associated with attendance at the facility; in such examples, the first set of data and / or the second set of data may comprise data representative of a title and / or job code.

[0111] In one or more examples, the method 100 comprises obtaining S118, such as determining, based on the first data, the second data, and / or the third data, the metric associated with attendance at the facility; in such examples, the first set of data and / or the second set of data may comprise data representative of traffic, weather, employee(s), and / or an organization, such as an organization of the person with access rights for the facility.

[0112] The method 100 comprises modifying S120, based on, for example, the second data and / or third data, the first data.

[0113] In one or more examples, modifying the first data comprises generating S120A fourth data, such as by applying a machine learning model to the second data and / or third data.

[0114] In one or more examples, the fourth data comprise a modified version of the first data.

[0115] In one or more examples, the machine learning model comprises an additive regression model and / or a temporal fusion transformer.

[0116] In one or more examples, the method 100 comprises modifying the first data and / or the second data, such as based on comparing S120B the second data and / or additional data (for example, third data and / or fourth data) associated with the at least one other person with different access rights for the facility.

[0117] In one or more examples, the method 100 comprises modifying the first data and / or the second data, such as based on a determining S120C whether a criterion, such as a criterion associated with the attendance policy, is met. In one or more examples, a criterion associated with the attendance policy is a parameter of the attendance policy. In one or more examples, a criterion associated with the attendance policy is specified bythe attendance policy and / or is based on or inferred from a parameter of the attendance policy.

[0118] In one or more examples, the method 100 comprises modifying S120D the first data and / or the second data, such as based on the turnover parameter.

[0119] In one or more examples, modifying the first data and / or the second data comprises changing S120E an office attendance policy, such as based on a fourth parameter indicative of an organization, an employee, a title, and / or a job code.

[0120] In one or more examples, the method 100 comprises modifying S120F the first data and / or the second data, such as based on the emission parameter, such as carbon dioxide emission parameter.

[0121] In one or more examples, the method 100 comprises modifying S120G the first data and / or the second data, such as based on a commuting distance for at least one person. A commuting distance may be seen as a quantifiable distance, such as a distance measured in kilometers and / or miles, of a commuting route.

[0122] In some examples, whether one or more of the productivity parameter, the turnover parameter, the emissions parameter, the commuting parameter, and the fourth parameter satisfy the criterion depends on whether one or more of the productivity parameter, the turnover parameter, the emissions parameter, the commuting parameter, and the fourth parameter are greater than or equal to the threshold.

[0123] For example, when one or more of the productivity parameter, the turnover parameter, the emissions parameter, the commuting parameter, and the fourth parameter are greater than or equal to the threshold, the criterion can be seen as being satisfied. In some examples, when the criteria are satisfied the electronic device may proceed with carrying out the method 100, such as modifying the first data.

[0124] For example, when one or more of the productivity parameter, the turnover parameter, the emissions parameter, the commuting parameter, and the fourth parameter are less than the threshold, the criterion can be seen as not being satisfied by the document quality score. In some examples, when the criteria are not satisfied the electronic devicemay refrain from carrying out the method 100, such as refrain from modifying the first data.

[0125] In one or more examples, the method 100 comprises determining S122, such as based on the modified first data, control data for controlling the third electronic device. Control data as disclosed herein may for example be seen as data used for controlling a device, such as an electronic device. In other words, an electronic device (such as the third electronic device) may be controlled based on the control data. The control data may for example be indicative of one or more actions (such as operations) to be performed, such as by the third electronic device.

[0126] In one or more examples, the method 100 comprises controlling S124, such as based on the control data, the third electronic device. For example, controlling S124 the third electronic device may comprise controlling the provision of an output, such as display, from the third electronic device. In other words, controlling S124 the third electronic device may comprise causing the third electronic device to provide, such as output, the modified first data (such as to another electronic device and / or to a user of the third electronic device).

[0127] In some examples, controlling S124 the third electronic device comprises requesting first data, second data, and / or third data (such as updated first, second, and / or third data) from the third electronic device, such as via the link 10B shown in Fig. 1.

[0128] Fig. 3 shows a block diagram of an example electronic device 300 according to the disclosure. The electronic device 300 comprises memory circuitry 301 , processor circuitry 302, and an interface 303, which may be wired or wireless. In one or more examples, electronic device 300 comprises a user interface 304, such as a graphical user interface or an interface for a peripheral device. In one or more examples, the electronic device comprises another input interface 305, such as a card reader, RFID reader, and / or NFC transceiver. The electronic device 300 may be configured to perform any of the methods disclosed herein, such as any of the methods described with reference to Figs. 2A-2B. In other words, the electronic device 300 may be configured for managing systems of a facility. Electronic device 300 may be referred to as a first electronic device, in one or more examples, which may be configured to communicate with and / or control one ormore additional electronic devices (such as second or third electronic devices), which may be electronic devices 400 described with reference to Fig. 1.

[0129] In one or more examples, the electronic device 300 is configured to receive, such as via interface 303 and / or via processing circuitry 302 from memory circuitry 301 , a first set of data comprising first data associated with the facility. In one or more examples, the electronic device is configured to receive the first data, such as the first set of data, via user interface 304 and / or input interface 305. In one or more examples, the first data comprise one or more attendance parameters associated with an attendance policy. In one or more examples, the first data comprise one or more historical attendance parameters associated with an historical attendance record and / or a calendar day parameter associated with designated calendar days. The first set of data may comprise data associated with at least one of a quantity of workstations, a quantity of seats, a designated location of one or more employees, or a quantity of employees, or any combination thereof. Additionally or alternatively, the first set of data may comprise data representative of a title, a role within the facility, a security clearance, a seniority level, an employment status, an immigration or citizenship status, a job code, a job function, a professional credential, an identification, an ability, a location, a time zone, a telephone number, or any combination thereof.

[0130] In one or more examples, the electronic device 300 is configured to receive, such as via interface 303 and / or via processing circuitry 302 from memory circuitry 301 , a second set of data comprising second data, such as second data associated with at least one person with access rights for the facility. In one or more examples, the electronic device is configured to receive the second data, such as the second set of data, via user interface 304 and / or input interface 305. In one or more examples, the second data comprise updated second data. Additionally or alternatively, the second set of data may comprise a permission indicator for logging access to at least one resource of the facility.

[0131] In one or more examples, the second data comprise data exported from another system associated with the facility. The second data may be exported from the employee time reporting system.

[0132] In one or more examples, the second data comprise data representative of address information for the at least one person with access rights for the facility. The second datamay comprise, such as additionally comprise, data representative of a transportation mode and / or a commuting route for the at least one person with access rights for the facility. In one or more examples, the second set of data comprises data representative of at least one of a survey, an exit interview, timekeeping, or payroll, or any combination thereof. Additionally or alternatively, the second set of data may comprise data associated with at least one other person with different access rights to the facility.

[0133] In one or more examples, the electronic device 300 is configured to, such as via interface 301 and / or via processing circuitry 302 from memory circuitry 301, receive third data indicative of an occupancy rate for at least one portion of the facility. In one or more examples, the electronic device receives the third data via user interface 304 and / or input interface 305. In one or more examples, the third data comprise updated third data.

[0134] In one or more examples, the electronic device 300 is configured to modify, such as via processor circuitry 302 and / or memory circuitry 301, the first data. Such modification may be based on the second and / or third data.

[0135] In one or more examples, the electronic device 300 is configured to generate, such as with processor circuitry 302 and / or memory circuitry 301 , fourth data. In one or more examples, processor circuitry 302 and / or memory circuitry 301 may generate fourth data by applying a machine learning model to the second data and / or third data. In one or more examples, the machine learning model comprises an additive regression model and / or a temporal fusion transformer. In one or more examples, the fourth data comprise a modified version of the first data. Memory circuitry 301 may store (for example, may be configured to store) machine learning models and / or training data.

[0136] The memory circuitry 301 may be configured to store some or all of the first data, such as the first data set, the second data, such as the second data set, third data, and / or fourth data. The memory circuitry 301 may store additional data in some examples.

[0137] In one or more examples, the electronic device 300 is configured to determine, such as via processor circuitry 302, at least one resource associated with the facility. In one or more examples, the first set of data comprises data associated with the at least one resource. In one or more examples, the at least one resource comprises at least one of a designated portion of the facility, a room, a portion of a room, office equipment, laboratoryequipment, audio / visual equipment, food service equipment, collaboration tools, exercise equipment, machinery, an accessibility tool, or a vehicle, or any combination thereof. The at least one resource may comprise a unique identifier indicative of the at least one resource.

[0138] In one or more examples, the electronic device 300 is configured to receive, such as via interface 303, the first data from an external device (such as an electronic device 400 of Fig. 1) via the Internet.

[0139] In one or more examples, the electronic device 300 is couplable with another system associated with the facility, such as an employee time reporting system, such as via interface 303 and / or input interface 305. The first set of data may comprise first data and / or the second set of data may comprise second data exported from the employee time reporting system.

[0140] The electronic device 300 may be couplable with a WLAN of a facility, and may receive data, such as first data, second data, and / or third data via the WLAN. In one or more examples, the electronic device 300 is configured to receive data based on, such as related to or indicative of, access to the WLAN, such as employee access to the WLAN. In one or more examples, the electronic device 300 is configured to receive data based, such as related to or indicative of, access to on a Bluetooth connection, a Zigbee connection, an RFID connection, or an NFC connection, or any combination thereof.

[0141] In one or more examples, the electronic device 300 is configured to modify, such as with processor circuitry 302 and / or memory circuitry 301 , the first data and / or the second data based on, for example, comparing the second data and additional data associated with the at least one other person with different access rights for the facility.

[0142] In one or more examples, the electronic device 300 is configured to receive, such as via interface 303, user interface 304, and / or input interface 305, the second data from another (for example, third) electronic device, such as an electronic device associated with the at least one person with access rights to the facility and / or with another person with different access rights.

[0143] In one or more examples, the electronic device 300 is configured to modify, such as with processor circuitry 302 and / or memory circuitry 301, the first data based on, such asbased in part on, a productivity parameter. In one or more examples, the second set of data comprises a productivity parameter associated with a productivity of one or more persons and / or organizations associated with the facility.

[0144] In one or more examples, the electronic device 300 is configured to modify, such as with processor circuitry 302 and / or memory circuitry 301 , the first data and / or the second data based on a determining whether a criterion is met, such as a criterion associated with the attendance policy.

[0145] In one or more examples, the electronic device 300 is configured to determine, such as with processor circuitry 302 and / or memory circuitry 301 , a turnover parameter associated with employee turnover based on the second data and / or the third data. In one or more examples, the electronic device is configured to modify, such as with processor circuitry 302 and / or memory circuitry 301 , the first data and / or the second data based on the turnover parameter.

[0146] In one or more examples, the electronic device 300 is configured to modify, such as with processor circuitry 302 and / or memory circuitry 301 , the first data and / or the second data by changing an office attendance policy, such as based on a fourth parameter indicative of an organization, an employee, a title, and / or a job code.

[0147] In one or more examples, the electronic device 300 is configured to determine, such as with processor circuitry 302 and / or memory circuitry 301 , an emission parameter associated with carbon dioxide emissions based on the second data and / or the third data. In one or more examples, the electronic device is configured to modify, such as with processor circuitry 302 and / or memory circuitry 301 , the first data and / or the second data based on the emission parameter.

[0148] In one or more examples, the electronic device 300 is configured to modify, such as with processor circuitry 302 and / or memory circuitry 301 , the first data and / or the second data based on a commuting distance, such as a commuting distance for the at least one person with access rights for the facility and / or another person associated with the facility, which may be represented in and / or communicated via the second data set, such as via second data.In one or more examples, the electronic device 300 is configured to obtain, such as with interface 303, user interface 304, input interface 305, and / or processor circuitry 302, a commuting parameter, such as a commuting parameter associated with a commuting cost for the at least one person with access rights for the facility. The commuting parameter may be obtained, for example, based on the first data, the second data, and / or the third data.

[0149] In one or more examples, the electronic device 300 is configured to obtain, such as with interface 303, user interface 304, input interface 305, and / or processor circuitry 302, a metric associated with attendance at the facility. The metric may be obtained, for example, based on the first data, the second data, and / or the third data. In one or more examples, the second set of data comprises data representative of a title and / or a job code. In one or more examples, the first set of data and / or the second set of data comprise data representative of traffic, weather, employees, and / or an organization of the person with access rights for the facility.

[0150] In one or more examples, the electronic device 300 is configured to receive, such a via interface 303, user interface 304, and / or input interface 305, the second data, for example, from a second electronic device (such as an electronic device 400 of Fig. 1) that comprises at least one of an occupancy sensor, a card reader, a fob reader, an access point, a keypad, a network node, a wireless router, a server, a camera, a biometric identifier, a facial recognition system, a quick response, QR, code reader, a proximity sensor, a wearable electronic device, a mobile phone, a tablet, or a computer, or any combination thereof.

[0151] In one or more examples, the electronic device 300 is configured to determine, such as with processor circuitry 302, such as based on the modified first data, control data for controlling a third electronic device (such as an electronic device 400 of Fig. 1).

[0152] In one or more examples, the electronic device 300 is configured to control, such a via interface 303, such as based on the control data, another (for example, third) electronic device (such as an electronic device 400 of Fig. 1).

[0153] The interface 303 may be configured for wired communications, such as via USB, HDMI, Ethernet, coaxial, and / or fiber optic cabling. The interface 303 may be configured forwireless communications, such as via a wireless communication system, such as a 3GPP system, such as a 3GPP system supporting one or more of: New Radio, NR, Narrowband loT, NB-loT, and Long Term Evolution - enhanced Machine Type Communication, LTE-M.

[0154] The electronic device 300 is optionally configured to perform any of the operations disclosed in and / or described with reference to Figs. 2A-2B (such as any one or more of S101, S102, S104, S106, S110, S112, S114, S116, S118, S120, S122, and / orS124). The operations of the electronic device 300 may be embodied in the form of executable logic routines (for example, lines of code, software programs, etc.) that are stored on a non-transitory computer readable medium (for example, memory circuitry 301) and are executed by processor circuitry 302.

[0155] Furthermore, the operations of the electronic device 300 may be considered a method that the electronic device 300 is configured to carry out. Also, while the described functions and operations may be implemented in software, such functionality may as well be carried out via dedicated hardware or firmware, or some combination of hardware, firmware and / or software.

[0156] Memory circuitry 301 may be one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, a random access memory (RAM), or another suitable device. In a typical arrangement, memory circuitry 301 may include a non-volatile memory for long term data storage and a volatile memory that functions as system memory for processor circuitry 302. Memory circuitry 301 may exchange data with processor circuitry 302 over a data bus. Control lines and an address bus between memory circuitry 301 and processor circuitry 302 also may be present (not shown in Fig. 3). Memory circuitry 301 is considered a non-transitory computer readable medium.

[0157] Memory circuitry 301 may be configured to store information (such as first data, the first set of data, second data, the second set of data, third data, and / or fourth data, for example, as described with reference to the method(s) depicted in Fig. 2A-2B or elsewhere herein) in a part of the memory.Embodiments of methods, devices, apparatuses, and / or products according to the disclosure are set out in the following items:

[0158] Item 1. A method, performed by a first electronic device, for managing systems of a facility, the method comprising:

[0159] receiving a first set of data comprising first data associated with the facility; receiving a second set of data comprising second data associated with at least one person with access rights for the facility;

[0160] receiving third data indicative of an occupancy rate for at least one portion of the facility; and

[0161] modifying, based on the second data, and / or third data, the first data. Item 2. The method according to item 1 , wherein the first data comprise one or more attendance parameters associated with an attendance policy.

[0162] Item 3. The method according to any of the preceding items, wherein modifying the first data comprises generating fourth data, by applying a machine learning model to the second data and / or third data (such as an additive regression model and / or a temporal fusion transformer), and wherein the fourth data comprise a modified version of the first data.

[0163] Item 4. The method according to item 3, wherein the second data comprise updated second data and / or the third data comprise updated third data.

[0164] Item 5. The method according to any of the preceding items, wherein the first data comprise one or more historical attendance parameters associated with an historical attendance record and / or a calendar day parameter associated with designated calendar days.

[0165] Item 6. The method according to any of the preceding items, the method comprising:

[0166] determining at least one resource associated with the facility, wherein the first set of data comprises data associated with the at least one resource. Item 7. The method according to item 6, wherein the at least one resource comprises at least one of a designated portion of the facility, a room, a portion of aroom, office equipment, laboratory equipment, audio / visual equipment, food service equipment, collaboration tools, exercise equipment, machinery, an accessibility tool, or a vehicle, or any combination thereof.

[0167] Item 8. The method according to any of items 6-7, wherein the at least one resource comprises a unique identifier indicative of the at least one resource.

[0168] Item 9. The method according to any of the preceding items, wherein the first set of data comprises data associated with at least one of a quantity of workstations, a quantity of seats, a designated location of one or more employees, or a quantity of employees, or any combination thereof.

[0169] Item 10. The method according to any of the preceding items, wherein the first set of data comprises data representative of a title, a role within the facility, a security clearance, a seniority level, an employment status, an immigration or citizenship status, a job code, a job function, a professional credential, an identification, an ability, a location, a time zone, a telephone number, or any combination thereof. Item 11. The method according to any of the preceding items, wherein the first data is received from an external device via the Internet.

[0170] Item 12. The method according to any of the preceding items, wherein the first set of data comprises first data exported from an employee time reporting system.

[0171] Item 13. The method according to any of the preceding items, the method comprising:

[0172] receiving the first data via a user interface of the first electronic device.

[0173] Item 14. The method according to any of the preceding items, wherein the second set of data comprises a permission indicator for logging access to at least one resource of the facility.

[0174] Item 15. The method according to item 14, wherein the at least one resource comprises a wireless local area network, WLAN, associated with the facility.

[0175] Item 16. The method according to item 15, wherein the third data is based on access to the WLAN.

[0176] Item 17. The method according to any of the preceding items, wherein the second data comprise data exported from another system associated with the facility.Item 18. The method according to item 17, wherein the second data is exported from the employee time reporting system.

[0177] Item 19. The method according to any of the preceding items, wherein the second data comprise data representative of address information for the at least one person with access rights for the facility.

[0178] Item 20. The method according to any of the preceding items, wherein the second data comprise data representative of a transportation mode and / or a commuting route for the at least one person with access rights for the facility.

[0179] Item 21. The method according to any of the preceding items, wherein the second set of data comprises data representative of at least one of a survey, an exit interview, timekeeping, or payroll, or any combination thereof.

[0180] Item 22. The method according to any of the preceding items, wherein the second set of data comprises data associated with at least one other person with different access rights to the facility.

[0181] Item 23. The method according to item 22, the method comprising:

[0182] modifying the first data and / or the second data based on comparing the second data and additional data associated with the at least one other person with different access rights for the facility.

[0183] Item 24. The method according to any of the preceding items, the method comprising:

[0184] receiving the second data from a third electronic device associated with the at least one person with access rights to the facility and / or with another person with different access rights.

[0185] Item 25. The method according to any of the preceding items, wherein the second set of data comprises a productivity parameter associated with a productivity of one or more persons and / or organizations associated with the facility.

[0186] Item 26. The method according to any of the preceding items, wherein the first set of data comprises a criterion associated with the attendance policy, the method comprising:modifying the first data and / or the second data based on a determining whether the criterion is met.

[0187] Item 27. The method according to any of the preceding items, the method comprising:

[0188] determining a turnover parameter associated with employee turnover based on the second data and / or the third data; and

[0189] modifying the first data and / or the second data based on the turnover parameter.

[0190] Item 28. The method according to any of the preceding items, wherein modifying the first data and / or the second data comprises changing an office attendance policy based on a fourth parameter indicative of an organization, an employee, a title, and / or a job code.

[0191] Item 29. The method according to any of the preceding items, the method comprising:

[0192] determining an emission parameter associated with carbon dioxide emissions based on the second data and / or the third data; and

[0193] modifying the first data and / or the second data based on the emission parameter.

[0194] Item 30. The method according to any of the preceding items, wherein the second set of data comprises data representative of a commuting distance for the at least one person with access rights for the facility and / or another person associated with the facility, the method comprising:

[0195] modifying the first data and / or the second data based on the commuting distance.

[0196] Item 31. The method according to any of the preceding items, wherein the second set of data comprises data representative of a commuting distance, a transportation mode, and / or a traffic condition, the method comprising:

[0197] obtaining, based on the first data, the second data, and / or the third data, a commuting parameter associated with a commuting cost for the at least one person with access rights for the facility.Item 32. The method according to any of the preceding items, wherein the second set of data comprises data representative of a title and / or a job code, the method comprising:

[0198] obtaining, based on the first data, the second data, and / or the third data, a metric associated with attendance at the facility.

[0199] Item 33. The method according to any of the preceding items, wherein the first set of data and / or the second set of data comprise data representative of traffic, weather, employees, and / or an organization of the person with access rights for the facility, the method comprising:

[0200] obtaining, based on the first data, the second data, and / or the third data, the metric associated with attendance at the facility.

[0201] Item 34. The method according to any of the preceding items, wherein the second data comprises data from a second electronic device comprising at least one of an occupancy sensor, a card reader, a fob reader, an access point, a keypad, a network node, a wireless router, a server, a camera, a biometric identifier, a facial recognition system, a quick response, QR, code reader, a proximity sensor, a wearable electronic device, a mobile phone, a tablet, or a computer, or any combination thereof.

[0202] Item 35. The method according to any of the preceding items, wherein the method comprises determining, based on the modified first data, control data for controlling the third electronic device.

[0203] Item 36. The method according to item 35, wherein the method comprises controlling, based on the control data, the third electronic device.

[0204] Item 37. A first electronic device for managing systems of a facility, the first electronic device comprising memory circuitry and processor circuitry, the first electronic device configured to:

[0205] receive a first set of data comprising first data associated with the facility; receive a second set of data comprising second data associated with at least one person with access rights for the facility;receive third data indicative of an occupancy rate for at least one portion of the facility; and

[0206] modify, based on the second data, and / or third data, the first data.

[0207] Item 38. The first electronic device according to item 37, wherein the first data comprise one or more attendance parameters associated with an attendance policy.

[0208] Item 39. The first electronic device according to any of items 37-38, the first electronic device configured to generate fourth data by applying a machine learning model (such as an additive regression model and / or a temporal fusion transformer) to the second data and / or third data, and wherein the fourth data comprise a modified version of the first data.

[0209] Item 40. The first electronic device according to item 39, wherein the second data comprise updated second data and / or the third data comprise updated third data. Item 41. The first electronic device according to any of items 37-40, wherein the first data comprise one or more historical attendance parameters associated with an historical attendance record and / or a calendar day parameter associated with designated calendar days.

[0210] Item 42. The first electronic device according to any of items 37-41 , the first electronic device configured to:

[0211] determine at least one resource associated with the facility, wherein the first set of data comprises data associated with the at least one resource.

[0212] Item 43. The first electronic device according to item 42, wherein the at least one resource comprises at least one of a designated portion of the facility, a room, a portion of a room, office equipment, laboratory equipment, audio / visual equipment, food service equipment, collaboration tools, exercise equipment, machinery, an accessibility tool, or a vehicle, or any combination thereof.

[0213] Item 44. The first electronic device according to any of items 42-43, wherein the at least one resource comprises a unique identifier indicative of the at least one resource.Item 45. The first electronic device according to any of items 37-44, wherein the first set of data comprises data associated with at least one of a quantity of workstations, a quantity of seats, a designated location of one or more employees, or a quantity of employees, or any combination thereof.

[0214] Item 46. The first electronic device according to any of items 37-45, wherein the first set of data comprises data representative of a title, a role within the facility, a security clearance, a seniority level, an employment status, an immigration or citizenship status, a job code, a job function, a professional credential, an identification, an ability, a location, a time zone, a telephone number, or any combination thereof.

[0215] Item 47. The first electronic device according to any of items 37-46, first electronic device configured to receive the first data from an external device via the Internet. Item 48. The first electronic device according to any of items 37-47, wherein the first set of data comprises first data exported from an employee time reporting system. Item 49. The first electronic device according to any of items 37-48, the first electronic device configured to receive the first data via a user interface.

[0216] Item 50. The first electronic device according to any of items 37-49, wherein the second set of data comprises a permission indicator for logging access to at least one resource of the facility.

[0217] Item 51. The first electronic device according to item 50, wherein the at least one resource comprises a wireless local area network, WLAN, associated with the facility.

[0218] Item 52. The first electronic device according to item 51 , wherein the third data is based on access to the WLAN.

[0219] Item 53. The first electronic device according to any of items 37-52, wherein the second data comprise data exported from another system associated with the facility.

[0220] Item 54. The first electronic device according to item 53, wherein the second data is exported from the employee time reporting system.Item 55. The first electronic device according to any of items 37-54, wherein the second data comprise data representative of address information for the at least one person with access rights for the facility.

[0221] Item 56. The first electronic device according to any of items 37-55, wherein the second data comprise data representative of a transportation mode and / or a commuting route for the at least one person with access rights for the facility. Item 57. The first electronic device according to any of items 37-56, wherein the second set of data comprises data representative of at least one of a survey, an exit interview, timekeeping, or payroll, or any combination thereof.

[0222] Item 58. The first electronic device according to any of items 37-57, wherein the second set of data comprises data associated with at least one other person with different access rights to the facility.

[0223] Item 59. The first electronic device according to item 58, the first electronic device configured to modify the first data and / or the second data based on comparing the second data and additional data associated with the at least one other person with different access rights for the facility.

[0224] Item 60. The first electronic device according to any of items 37-59, the first electronic device configured to receive the second data from a third electronic device associated with the at least one person with access rights to the facility and / or with another person with different access rights.

[0225] Item 61. The first electronic device according to any of items 37-60, wherein the second set of data comprises a productivity parameter associated with a productivity of one or more persons and / or organizations associated with the facility.

[0226] Item 62. The first electronic device according to any of items 37-61 , wherein the first set of data comprises a criterion associated with the attendance policy, the first electronic device configured to modify the first data and / or the second data based on a determining whether the criterion is met.

[0227] Item 63. The first electronic device according to any of items 37-62, the first electronic device configured to:determine a turnover parameter associated with employee turnover based on the second data and / or the third data; and

[0228] modify the first data and / or the second data based on the turnover parameter. Item 64. The first electronic device according to any of items 37-63, first electronic device configured to modify the first data and / or the second data by changing an office attendance policy based on a fourth parameter indicative of an organization, an employee, a title, and / or a job code.

[0229] Item 65. The first electronic device according to any of items 37-64, the first electronic device configured to:

[0230] determine an emission parameter associated with carbon dioxide emissions based on the second data and / or the third data; and

[0231] modify the first data and / or the second data based on the emission parameter. Item 66. The first electronic device according to any of items 37-65, wherein the second set of data comprises data representative of a commuting distance for the at least one person with access rights for the facility and / or another person associated with the facility, the first electronic device configured to modify the first data and / or the second data based on the commuting distance.

[0232] Item 67. The first electronic device according to any of items 37-66, wherein the second set of data comprises data representative of a commuting distance, a transportation mode, and / or a traffic condition, the first electronic device configured to obtain, based on the first data, the second data, and / or the third data, a commuting parameter associated with a commuting cost for the at least one person with access rights for the facility.

[0233] Item 68. The first electronic device according to any of items 37-67, wherein the second set of data comprises data representative of a title and / or a job code, the first electronic device configured to obtain, based on the first data, the second data, and / or the third data, a metric associated with attendance at the facility. Item 69. The first electronic device according to any of items 37-68, wherein the first set of data and / or the second set of data comprise data representative of traffic, weather, employees, and / or an organization of the person with access rights for the facility, the first electronic device configured to obtain, based on the first data,the second data, and / or the third data, the metric associated with attendance at the facility.

[0234] Item 70. The first electronic device according to any of items 37-69, wherein the first electronic device is configured to receive the second data from a second electronic device that comprises at least one of an occupancy sensor, a card reader, a fob reader, an access point, a keypad, a network node, a wireless router, a server, a camera, a biometric identifier, a facial recognition system, a quick response, QR, code reader, a proximity sensor, a wearable electronic device, a mobile phone, a tablet, or a computer, or any combination thereof.

[0235] Item 71. The first electronic device according to any of items 37-70, the first electronic device configured to determine, based on the modified first data, control data for controlling the third electronic device.

[0236] Item 72. The first electronic device according to item 71 , the first electronic device configured to control, based on the control data, the third electronic device.

[0237] The use of the terms “first”, “second”, “third” and “fourth”, “primary”, “secondary”, “tertiary” etc. does not imply any particular order, but are included to identify individual elements. Moreover, the use of the terms “first”, “second”, “third” and “fourth”, “primary”, “secondary”, “tertiary” etc. does not denote any order or importance, but rather the terms “first”, “second”, “third” and “fourth”, “primary”, “secondary”, “tertiary” etc. are used to distinguish one element from another. Note that the words “first”, “second”, “third” and “fourth”, “primary”, “secondary”, “tertiary” etc. are used here and elsewhere for labelling purposes only and are not intended to denote any specific spatial or temporal ordering. Furthermore, the labelling of a first element does not imply the presence of a second element and vice versa.

[0238] It may be appreciated that Figs. 1-3 comprises some circuitries or operations which are illustrated with a solid line and some circuitries or operations which are illustrated with a dashed line. Circuitries or operations which are comprised in a solid line are circuitries or operations which are comprised in the broadest example embodiment. Circuitries or operations which are comprised in a dashed line are example embodiments which may be comprised in, or a part of, or are further circuitries or operations which may be taken in addition to circuitries or operations of the solid line example embodiments. It should be appreciated that these operations need not be performed in order presented.Furthermore, it should be appreciated that not all of the operations need to be performed. The example operations may be performed in any order and in any combination.

[0239] It is to be noted that the word "comprising" does not necessarily exclude the presence of other elements or steps than those listed.

[0240] It is to be noted that the words "a" or "an" preceding an element do not exclude the presence of a plurality of such elements.

[0241] It is to be noted that a list in the form of “at least one of A, B, or C, or any combination thereof” should be understood to mean “A”, or “B”, or “C”, or “A and B”, or “A and C”, or “B and C”, or “A and B and C”.

[0242] It should further be noted that any reference signs do not limit the scope of the claims, that the example embodiments may be implemented at least in part by means of both hardware and software, and that several "means", "units" or "devices" may be represented by the same item of hardware.

[0243] The various example methods, devices, nodes and systems described herein are described in the general context of method steps or processes, which may be implemented in one aspect by a computer program product, embodied in a computer-readable medium, including computer-executable instructions, such as program code, executed by computers in networked environments. A computer-readable medium may include removable and non-removable storage devices including, but not limited to, Read Only Memory (ROM), Random Access Memory (RAM), compact discs (CDs), digital versatile discs (DVD), etc. Generally, program circuitries may include routines, programs, objects, components, data structures, etc. that perform specified tasks or implement specific abstract data types. Computer-executable instructions, associated data structures, and program circuitries represent examples of program code for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps or processes.

[0244] Although features have been shown and described, it will be understood that they are not intended to limit the claimed disclosure, and it will be made obvious to those skilled in the art that various changes and modifications may be made without departing from the scopeof the claimed disclosure. The specification and drawings are, accordingly, to be regarded in an illustrative rather than restrictive sense. The claimed disclosure is intended to cover all alternatives, modifications, and equivalents.

Claims

43CLAIMS1. A method (100), performed by a first electronic device, for managing systems of a facility, the method comprising:receiving (S102) a first set of data comprising first data associated with the facility, wherein the first data comprise one or more attendance parameters associated with an attendance policy;receiving (S104) a second set of data comprising second data associated with at least one person with access rights for the facility;receiving (S106) third data indicative of an occupancy rate for at least one portion of the facility; andmodifying (S120), based on the second data and / or third data, the first data.

2. The method according to claim 1 , wherein modifying the first data comprises generating fourth data, by applying a machine learning model to the second data and / or third data, wherein the fourth data comprise a modified version of the first data.

3. The method according to claim 1 , wherein the first data comprise one or more historical attendance parameters associated with an historical attendance record and / or a calendar day parameter associated with designated calendar days.

4. The method according to claim 1 , the method comprising:determining (S101 ) at least one resource associated with the facility, wherein the first set of data comprises data associated with the at least one resource.

5. The method according to claim 1 , wherein the first set of data comprises data representative of a title, a role within the facility, a security clearance, a seniority level, an employment status, an immigration or citizenship status, a job code, a job function, a professional credential, an identification, an ability, a location, a time zone, a telephone number, or any combination thereof.

6. The method according to claim 1 , wherein the first data is received from an external device via the Internet.

447. The method according to claim 1 , wherein the first set of data comprises first data exported from an employee time reporting system.

8. The method according to claim 1 , the method comprising:receiving the first data via a user interface of the first electronic device.

9. The method according to claim 1 , wherein the second set of data comprises a permission indicator for logging access to at least one resource of the facility.

10. The method according to claim 1 , wherein the second data comprise data representative of address information for the at least one person with access rights for the facility; and / or data representative of a transportation mode and / or a commuting route for the at least one person with access rights for the facility.

11. The method according to claim 1 , wherein the second set of data comprises data representative of at least one of a survey, an exit interview, timekeeping, or payroll, or any combination thereof; and / or data associated with at least one other person with different access rights to the facility.

12. The method according to claim 1 , the method comprising:receiving the second data from a third electronic device associated with the at least one person with access rights to the facility and / or with another person with different access rights.

13. The method according to claim 1 , wherein the second set of data comprises data representative of a commuting distance for the at least one person with access rights for the facility and / or another person associated with the facility, the method comprising:modifying the first data and / or the second data based on the commuting distance.

14. The method according to claim 1 , wherein the second set of data comprises data representative of a commuting distance, a transportation mode, and / or a traffic condition, the method comprising:45obtaining (S114), based on the first data, the second data, and / or the third data, a commuting parameter associated with a commuting cost for the at least one person with access rights for the facility.

15. The method according to claim 1 , wherein the second set of data comprises data representative of a title and / or a job code, the method comprising:obtaining (S116), based on the first data, the second data, and / or the third data, a metric associated with attendance at the facility.

16. The method according to claim 1 , wherein the first set of data and / or the second set of data comprise data representative of traffic, weather, employees, and / or an organization of the person with access rights for the facility, the method comprising:obtaining (S118), based on the first data, the second data, and / or the third data, the metric associated with attendance at the facility.

17. The method according to claim 1 , wherein the second data comprises data from a second electronic device comprising at least one of an occupancy sensor, a card reader, a fob reader, an access point, a keypad, a network node, a wireless router, a server, a camera, a biometric identifier, a facial recognition system, a quick response, QR, code reader, a proximity sensor, a wearable electronic device, a mobile phone, a tablet, or a computer, or any combination thereof.

18. The method according to claim 1, wherein the method comprises determining, based on the modified first data, control data for controlling the third electronic device.

19. The method according to claim 18, wherein the method comprises controlling, based on the control data, the third electronic device.

20. A first electronic device for managing systems of a facility, the first electronic device comprising memory circuitry and processor circuitry, the first electronic device configured to:receive a first set of data comprising first data associated with the facility, wherein the first data comprise one or more attendance parameters associated with an attendance policy;receive a second set of data comprising second data associated with at least one person with access rights for the facility;receive third data indicative of an occupancy rate for at least one portion of the facility; andmodify, based on the second data, and / or third data, the first data.

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