Technical Field

The present invention relates to systems and methods for use on construction sites. In particular, the systems or methods can be used for, but are not limited to, the detection of hazards and determining the progress of construction works on a construction site.

Background

Construction workers at construction sites are often at risk of several dangerous hazards. While safety procedures are in place on construction sites, human judgement errors, tiredness and complacency are pitfalls in upholding safety standards.

With the advent of computer vision and AI technology, detecting workers and equipment on construction sites enable augmented reality help in identifying if a worker is in a dangerous situation. Techniques such as proximity to dangerous objects and crowdedness of sites has been used to measure danger factors. Some systems are able to detect workers with no hardhat, safety harness and other personal protective equipment, unsafe actions of a worker on a ladder, poor body posture and so on.

Such systems typically rely on the placement of multiple fixed cameras on a jobsite, or the use of stereo vision cameras. These cameras need to be relocated when objects are positioned on the jobsites in locations that obscure the view of the cameras and, for multistorey construction sites, when construction of a higher floor commences.

Additionally, the depth dimension of a 3D scenario is lost when it is captured in a 2D camera image. It is hard to tell distance between objects and x, y, z location in space based using single 2D images. For construction sites, it is crucial to pinpoint hazardous areas or areas of concern in 3D, so they can be correctly bounded.

Stereo Vision can recover the depth dimension of the 3D scenario by using the disparity between 2 corresponding 2D images but the accuracy of depth estimation depends on the baseline distance required between 2 cameras. The baseline distance may be a set up problem on a construction site. Lidar technology has also been used to reconstruct the 3D scenarios of construction sites but the cost and processing time can be prohibitive particularly when urgent response actions need to be taken - e.g. where a worker is below an elevated load such as a load hanging from a crane.

In addition to detection of hazards, it is imperative that the progress of construction sites be monitored. To do this, a construction manager will often be on-site or sit behind a computer to view the structural and other members that are being brought onto site for installation. Such work can be highly mundane, resulting in decreased concentration and increased chance of failing to observe the arrival of some equipment or safety hazards on-site, and is not the best use of a construction manager's time.

It would be desirable to provide a method and/or system for detecting hazards and/or monitoring construction progress that overcomes one or more of the abovementioned drawbacks of the prior art, or at least provides a useful alternative.

Summary

Disclosed is a system for detecting a hazard, comprising: an image capture device mounted in an elevated position above a construction site; a mapping module; memory; and at least one processor, the memory storing instructions that, when executed by the at least one processor, cause the at least one processor to: capture, by the image capture device, an image of the construction site; identify at least one object in the image; determine, at the mapping module, a location of the at least one object on a floorplan of the construction site; and specifying presence or absence of the hazard relative to the floorplan based on the location of the at least one object.

There may be a first object, of the one or more objects, that is a first person. In this case, the at least one processor may be configured to specify presence or absence of the hazard based on the location of the human relative to a second object of the at least one object. The second object may be a second person. In this case, the at least one processor may be configured to specify presence or absence of the hazard based on a distance between the first person and the second person relative to a social distancing requirement applicable on the construction site.

The at least one object includes a construction object and the image capture device may be configured to capture a plurality of images of the construction site. In such embodiments, the one or more processors may be configured to identify at least one object in the image by identifying the construction object in two of more images of the plurality of images, and to locate two or more key points on the construction object. Presence or absence of the hazard can then be specified based on a relationship between the two or more key points.

The construction object may comprise a barrier and the at least one processor may be configured to identify the relationship by determining that a portion of the barrier is missing from between the two or more key points of the barrier. Presence of the hazard can then be defined as an area on the floorplan around a location of the portion, of the barrier, that is missing.

The relationship may instead, or in addition, be identified by detecting that the construction object is an elevated load. It can then be determined if the elevated load is above the construction site. By projecting a fall area onto the floorplan based on the two or more key points of the elevated load, presence of the hazard can be specified based on the fall area. Also disclosed is a system for determining construction site progress, comprising: an image capture device mounted in an elevated position above a construction site; a scheduling module comprising a schedule of items indicative of the construction site progress; memory; and at least one processor, the memory storing instructions that, when executed by the at least one processor, cause the at least one processor to: capture, by the image capture device, a plurality of images of the construction site; identify a load being moved onto site; make a comparison of the load with items in the schedule of items; and report, based on the comparison, the construction site progress.

The items in the schedule of items may form a sequence that follows a progression of works for progressing a construction site towards completion.

The instructions, when executed by the at least one processor, may also, or instead, cause the at least one processor to track a time for which the load has been lifted. Delays in depositing the load can be reported if the load has been hanging for longer than a threshold period.

Also disclosed herein is a method for detecting a hazard, comprising: capturing, by an image capture device mounted in an elevated position above a construction site, an image of the construction site; identifying at least one object in the image; determining, at a mapping module, a location of the at least one object on a floorplan of the construction site; and specifying presence or absence of the hazard relative to the floorplan based on the location of the at least one object.

The one or more objects may comprise a first person. The method in this instance can comprise specifying presence or absence of the hazard based on the location of the human relative to a second object of the at least one object. The second object may be a second person. The method in this instance can comprise specifying presence or absence of the hazard based on a distance between the first person and the second person relative to a social distancing requirement applicable on the construction site.

The at least one object may include a construction object. The method in such embodiments can include capturing an image of the construction site by capturing a plurality of images of the construction site. The construction object can be identified in two of more images of the plurality of images. By identifying the construction object in multiple images, two or more key points on the construction object can be tracked between images and presence or absence of the hazard can be specified based on a relationship between the two or more key points.

The construction object may comprise a barrier. The method may then include: identifying the relationship by determining that a portion of the barrier is missing from between the two or more key points of the barrier; and specifying presence of the hazard by defining an area on the floorplan around a location of the portion, of the barrier, that is missing.

Identifying the relationship may comprise detecting that the construction object is an elevated load, determining that the elevated load is above the construction site, and projecting a fall area onto the floorplan based on the two or more key points of the elevated load. In this case, presence of the hazard is specified based on the fall area.

Also disclosed is a method for determining construction site progress, comprising: capturing, by an image capture device mounted in an elevated position above a construction site, a plurality of images of the construction site; identifying a load being moved onto site; making a comparison of the load with items in a schedule of items, where the schedule of items are indicative of the construction site progress; and reporting, based on the comparison, the construction site progress. The items in the schedule of items may form a sequence, the sequence following a progression of works for progressing a construction site towards completion.

The method may further comprise tracking a time for which the load has been lifted, and reporting, based on the time, if the load has been hanging for longer than a threshold period.

In each of the above systems and methods, the image capture device may be mounted to a tower crane.

Advantageously, by mounting the image capture device to a tower crane, the position of the image capture device remains elevated above the construction site since the tower crane is extended as the height of the construction site grows.

In the prior art, systems for detecting missing barriers and the like were subject to false positives due to moving loads and other objects occasionally obscuring the view of those barriers and the like. Advantageously, embodiments of the present invention involves detecting the presence of barriers and other construction objects by reference to key points on or around those objects. In the event that those key points are not visible, the system may wait until the key points are identifiable before determining whether or not those barriers and other construction objects are missing. Alternatively, if no key points are visible - e.g. an entire side barrier has fallen - the system may detect absence of key points over such a length or area of the object that a hazard can be inferred.

Advantageously, embodiments of the present invention enable the remote and automated detection of social distancing breaches, as is resulting from the presence of suspended loads and the like.

Brief description of the drawings

Embodiments of the present invention will now be described, by way of non limiting example, with reference to the drawings in which:

Figure 1 is an exemplary computer system for performing the methods described herein;

Figure 2 illustrates changes in camera position relative to a construction site is the height of the construction site changes;

Figure 3 is a method for detecting a hazard at a construction site;

Figure 4 shows an image of a construction site in which bounding boxes have been placed around workers;

Figure 5 shows an image of a floorplan corresponding to the construction site of Figure 4, showing bounding boxes again surrounding various workers;

Figure 6 illustrates detection of the absence of a barrier, presently an object, by reference to key points surrounding the barrier;

Figure 7 shows a hazard area defined on a construction plane with reference to the absent barrier of Figure 6;

Figure 8 schematically illustrates the identification of a fall or drop zone on a construction plane beneath an elevated load;

Figure 9 is a method for monitoring construction site progress and tracking the time loads have remained elevated; and

Figure 10 is an image of a construction site of a high-rise construction project.

Detailed description

The present disclosure relates to the use of computer vision for monitoring workers on construction sites, safe distancing and other hazards, and construction floor progress. In some embodiments, the systems and methods are used for the detection of hazards on construction sites. These systems and methods leverage off an elevated camera position, and the use of a construction floorplan to accurately position people, objects and hazards. The system is enables the automated detection of hazards and the raising of alerts so that a construction manager, safety officer or other person can avoid constantly monitoring the job site.

A benefit of monitoring hazards using the present methods is the ability to monitor safe or social distancing (hereinafter "social distancing") between workers and, in particular, to identify when there has been a social distancing breach. Particularly during pandemics, there may be an expectation or legal requirement for jobsites to observe social distancing to minimize the risk of spreading disease. By detecting if a certain number of workers is too close to each other for a certain amount of time, a site supervisor can then make a decision to separate the congregation of workers or keep track of the temperature and movement of workers.

Also described are systems and methods for the monitoring of construction progress at a construction site. These systems and methods leverage off a known, predetermined schedule of items that are brought on-site at particular points in the construction process. Present systems and methods detect the arrival of these items as an indication of the current state of progress of construction. These systems and methods may also perform the hazard detection function.

The methods described herein can be implemented in a computer system such as system or device 100 in Figure 1. In particular, Figure 1 is a block diagram showing an exemplary computer device 100, in which embodiments of the invention may be practiced. The computer device 100 may be a mobile computer device such as a smart phone, a wearable device, a palm-top computer, and multimedia Internet enabled cellular telephones, an on-board computing system or any other computing system, a mobile device such as an iPhone ™ manufactured by Apple™, Inc or one manufactured by LG™, HTC™ and Samsung™, for example, or other device.

As shown, the mobile computer device 100 includes the following components in electronic communication via a bus 106:

(a) a display 102;

(b) non-volatile (non-transitory) memory 104;

(c) random access memory ("RAM") 108; (d) N processing components 110;

(e) a transceiver component 112 that includes N transceivers;

(f) user controls 114;

(g) a mapping module 118;

(h) a scheduling module 124; and

(i) image capture device - camera 120 .

Although the components depicted in Figure 1 represent physical components, Figure 1 is not intended to be a hardware diagram. Thus, many of the components depicted in Figure 1 may be realized by common constructs or distributed among additional physical components. Moreover, it is certainly contemplated that other existing and yet-to-be developed physical components and architectures may be utilized to implement the functional components described with reference to Figure 1.

The display 102 generally operates to provide a presentation of content to a user, and may be realized by any of a variety of displays (e.g., CRT, LCD, HDMI, micro projector and OLED displays).

In general, the non-volatile data storage 104 (also referred to as non-volatile memory) functions to store (e.g., persistently store) data and executable code. The system architecture may be implemented in memory 104, or by instructions stored in memory 104 - e.g. memory 104 may be a computer readable storage medium for storing instructions that, when executed by processor(s) 110 cause the processor(s) 110 to perform the methods 300 and 900 described with reference to Figures 3 and 9.

In some embodiments for example, the non-volatile memory 104 includes bootloader code, modem software, operating system code, file system code, and code to facilitate the implementation components, well known to those of ordinary skill in the art, which are not depicted nor described for simplicity.

In many implementations, the non-volatile memory 104 is realized by flash memory (e.g., NAND or ONENAND memory), but it is certainly contemplated that other memory types may be utilized as well. Although it may be possible to execute the code from the non-volatile memory 104, the executable code in the non-volatile memory 104 is typically loaded into RAM 108 and executed by one or more of the N processing components 110.

The N processing components 110 in connection with RAM 108 generally operate to execute the instructions stored in non-volatile memory 104. As one of ordinarily skill in the art will appreciate, the N processing components 110 may include a video processor, modem processor, DSP, graphics processing unit (GPU), and other processing components.

The transceiver component 112 includes N transceiver chains, which may be used for communicating with external devices via wireless networks. Each of the N transceiver chains may represent a transceiver associated with a particular communication scheme. For example, each transceiver may correspond to protocols that are specific to local area networks, cellular networks (e.g., a CDMA network, a GPRS network, a UMTS networks), and other types of communication networks.

The system 100 of Figure 1 may be connected to any appliance, such as a weather service for adjusting image recognition models to account for variations in weather, and the camera 120 may be physically separated from, but in communication with, the other components of the system.

The system 100 of Figure 1 also includes an image capture device, presently embodied by a camera 120 mounted at an elevated position above a construction site - though it will be appreciated that any appropriate image capture device may be used. The camera 120 captures images of the construction site that can then be cross-referenced, by mapping module 118, against a floorplan stored in or accessed by the mapping module 118 to locate objects on the floorplan. The camera 120 can also be used to capture images of loads being lifted by cranes or otherwise moved onto the construction site that can then be identified and cross- referenced, by scheduling module 124, against a schedule of items stored in or accessible by the scheduling module 124 to determine the progress of construction. It should be recognized that Figure 1 is merely exemplary and in one or more exemplary embodiments, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code encoded on a non-transitory computer-readable medium 104. Non-transitory computer-readable medium 104 includes both computer storage medium and communication medium including any medium that facilitates transfer of a computer program from one place to another. A storage medium may be any available medium that can be accessed by a computer.

The present system 100 deals directly with the setup of a construction site. In particular, while cameras for construction site monitoring can be mounted at various locations on the construction floor, camera 120 of Figure 1 is mounted on a tower crane that is used to lift loads onto the construction site. Such an arrangement is shown in Figure 2.

Camera 200 is connected to the mast 202 of tower crane 204. The camera 200 may instead be mounted on top of the tower crane, to the operators cab or at any other location from which to gain an elevated view of the construction site. As the height of the construction floor 206 changes. This is due to the tower crane 204 being extended each time the construction floor height changes.

From left to right in Figure 2, the height of the building 208 changes from 3 floors, to 4, then 6 and finally 7 floors or storeys. At each height change, the camera 200 remains in an elevated position above the floor. Also, for some changes in the height of the building 208, the camera remains sufficiently elevated above the construction floor 206 that there is no change in position of the camera despite a change in position of the construction floor.

Since the height of the camera 200 relative to the construction four 206 varies, the size of workers in images captured by the camera 200 can change. Workers may also look like humans all look like mounds or other objects depending on their body posture while working. Workers may also be occluded by construction objects such as moving or listed loads, reinforcement bar and other objects, or may be difficult to detect depending on illumination, inclement weather and other factors. This makes it difficult or impossible to calibrate some fixed cameras to detect the presence of workers.

The method 300 described with reference to Figure 3 may address these difficulties and enable accurate detection and tracking of workers on a construction floor, by fusing information derived from images captured by the camera 120 with a construction floorplan. The method 300 can be implemented on system 100, to detect a hazard on a construction site. The method 200 broadly includes:

Step 302 - capturing an image of the construction site;

Step 304 - identifying at least one object in the image captured at Step 302;

Step 306 - determining a location of the object on the floorplan of the construction site; and

Step 308 - specifying the presence or absence of a hazard on the floorplan based on the location determined at Step 306.

Step 302 involves capturing an image of the construction site using an image capture device such as camera 120, 200 mounted in an elevated position above a construction site. The image capture device may be a single camera, or system of image capture devices of any necessary type. Moreover, image capture device may only capture a single image or may capture a plurality of images such as a video feed.

Step 304 involves using the processor or processors 110 to identify objects in the image captured by the image capture device at Step 302. The objects can include a person whose safety is being monitored. The person is a safety will be monitored relative to some other object. For example, Step 304 may involve detecting the presence of multiple people on the construction site such that the distance between those people can be determined for the purpose of monitoring social distancing.

Construction workers vary in height and build. It can therefore be very difficult to ascertain the exact dimensions of each construction worker sized to properly monitor social distancing. On detecting a worker or person, the processor or processors 110 define a bounding box around that person. Step 306 involves determining, using mapping module 118, the location of each person on a floorplan of the construction site. That location may be defined by reference to the location of the bounding box defined at Step 304. Figure 4 shows the location of bounding boxes identifying workers on an image of a construction site 402, two of which have been labelled 400. Clearly, some bounding boxes 400 are closer together than others.

The mapping module 118 may store the floorplan of the construction site or may access it from a remote server or through any other means.

Landmarks in the images, such as fixed structural features of the construction site, that can be cross-referenced against the known locations of those landmarks on the floorplan. The locations of the objects, or of bounding boxes 400, may then be placed relative to the known locations on the floorplan based on the locations of those objects relative to the locations of the landmarks in the images captured at Step 302. Other image processing techniques may be used such as vanishing point isometric projection.

The placement of various workers or bounding boxes 400 is shown in Figure 5 on a floorplan 500. Since the dimensions of the floorplan are known to a high degree of certainty, the locations of the objects placed on the floorplan are also known to a high degree of certainty. Therefore, the location a person relative to a hazard, such as another person or elevated load, can be calculated to a high degree of accuracy.

Step 308 involves specifying the presence or absence of a hazard relative to the floorplan based on the location of the object or objects. Three groups of people 502 have been identified in Figure 5 is being sufficiently close to breach social distancing measures. The distances between all pairs of workers are calculated using a Euclidean Distance Matrix. Proximity to an unsafe area or condition may be specified by reference to a threshold distance, such as the social distancing minimum requirement specified for a particular construction site, and used effectively as a differentiator between the presence or absence of a hazard. In the event hazard is present, the system 100 may raise an alert per Step 310.

Step 302 may instead involve capturing multiple images. In general, this will constitute a video feed. Step 304 may then involve identifying a construction object in two or more of the images captured at Step 302. By identifying the construction object in multiple frames or images, a change in condition of the construction object can be detected. For example, when a protective barrier inadvertently comes down, it will appear in one frame but not in other frames. In this case, the system 100 may be configured to raise an alert according to Step 310.

Many loads and objects move around construction sites and can obscure the view of a camera, including objects being lifted by the tower crane to which the present camera may be attached, and the tower crane may shake. This can lead to false detections unsafe conditions. This circumstance can be avoided using the method 300, insofar as Step 306 can involve determining the location of a construction object on the floorplan (including the absence of that object from where the construction object should be, or a portion of that object) by locating two or more key points on the construction object and Step 308 involves specifying the presence or absence of a hazard based on a relationship between those key points.

In one example, if the construction object comprises a barrier (i.e. Step 304 involves identifying a single object), a portion of the barrier may be detected as missing from between key points of the barrier as a whole. To do this, barricades or barriers and other objects can be first detected using deep-learning segmentation techniques. Between frames or images, a previously detected barricade may go missing. The missing barricade can be detected since it is meant to be a static object yet it is present in some images and not in later images. Thus, rather than detect the barricade or barrier as a whole, Step 304 involves detecting four key points 600 of a missing barricade, or portion 602 of a barricade 604, as shown in Figure 6. In some embodiments, CenterNet is trained to detect these key points.

The key points 600 form a polygon that captures point locations 606. Her Step 304, the construction object is located by identifying the locations of these key points 600. With reference to Figure 7, according to Step 306 the point locations 606 are then located on the plane 608 corresponding to the construction floorplan area where the missing portion 602 of barricade is meant to be. For the purpose of defining a hazard area, construction floorplan may be represented by a plane grid. The distance between 2 point locations on the plane grid is calibrated to be, for example, a distance outside which there is considered to be no hazard and within which there is considered to be a hazard present. In the present embodiment, the plane grid set out points with 2m spacing. These grid points can be transformed onto the camera view. Hence, the distance between 2 point locations on the plane grid on the camera view is also 2m. The missing barricade is roughly at locations 606 on the plane grid. The surrounding locations 610 that are 1 point (presently 2m) away from the locations 606 are selected to define or specify, per Step 308, an area 612 that is within 2m of missing barricade and is marked as a hazard area.

In yet a further application of the method 300, the construction object may be an elevated load. Elevated loads are hazardous as they occasionally drop in can cause tremendous damage, injury or fatality in the fall area. In this embodiment, Step 304 may involve determining that the construction object is an elevated load and Step 306 may involve determining that the elevated load is above the construction site. This may occur before or after projecting fall area onto the floorplan using two or more key points, typically corners, of the elevated load.

The fall area may be projected from the elevated load onto the floorplan per Figure 8 by identifying the position of the elevated or lifted load 800 in three dimensions. Identifying the 3D position of the elevated load and workers though a 2D image is a major challenge as the third dimension, depth, is lost when the scene is capture by a camera as a 2D image. The present embodiment employs homography and an algorithm set out below to overcome this challenge. The algorithm for estimating area under load her Step 306 is as follows:

- Detect the key points 802 of the elevated load 800 - presently four corner points, /,, of the load using CenterNet Keypoint detection;

- Estimate the vanishing point 804, v,, of the scene - e.g. using Ransac algorithm. The vanishing point is a point vertically beneath the elevated load, and every other point in the scene, at theoretically infinite distance from the elevated load;

- Obtain a dropline vectors 806 for each key point 802, / = /,· - ¼. Each dropline vector is a vector connecting the load corners to the vanishing point;

- Detect class of load 800 to know the dimensions of the load according to a construction plan - for example, detection of a load of class "Householdshelter" gives the knowledge of the width and length of the lifted load based on the construction plane 812. The dimensions may be represented as a grid on the construction plane, two of which (808, 810) have been defined in the construction plane. Presently, the household shelter is a 2 by 3 grid.

- For each grid in the construction plane, find H, the sum of perpendicular distances from each grid corner point, g to each dropline, .

H = å _t=1 perpendicular distance of g _t /¼.

- The grid of appropriate dimensions - e.g. 2 x 3m for the Household shelter - having the smallest H, is the estimated area under load. The coordinates of the corner points of the grid may be stored, e.g. in memory 104.

The construction plane may correspond to the image taken by the image capture device 120, 200 or the construction floorplan, may be transformed onto the image from the image capture device and from there onto the construction floorplan, or may be transformed directly onto the construction floorplan.

Step 308 of method 300 then involves specifying the hazard area based on the full area. In particular, Step 308 involves specifying that a hazard is present if any worker is inside the area calculated as the area under load in Step 306. Step 310 may then be invoked to trigger an alert - e.g. an audible alarm, message to a construction manager mobile device or to the worker or workers inside the hazard area. The alert may include the location of the hazard area and/or the details of the worker or workers in that area.

With reference to Figure 9, the system 100 may also be used to implement a method 900 for determining construction site progress. The method 900 broadly comprises: Step 902: capturing multiple images of a construction site using an elevated camera such as camera 120, 200;

Step 904: identifying a load being moved onto site;

Step 906: making a comparison of the load with items in a schedule of items stored by or accessible to scheduling module 124; and Step 908: reporting construction site progress based on the outcome of the comparison made at Step 906.

Reporting progress of the construction floor towards completion is an essential step in effective management of a construction site. The method 900 can be used to automate some or all of this reporting process.

The schedule of items involved in the comparison at Step 906 lists a sequence of items and the sequence follows the progression of works for progressing a construction site towards completion (i.e. construction site or construction floor progress). The sequence of items enables domain knowledge to be fused with computer vision to monitor construction floor progress. In a high-rise context, six types of loads can often provide an accurate representation of the progress of the construction floor. The six loads are a lifting frame, household shelter, concrete bucket, precast plank, wall and window fagade.

Step 904 involves identifying the type of load being lifted onto the construction site. The load may be lifted from the crane on which the image capture device is mounted. Once the type of the load has been detected it can be compared, at Step 906, to the sequence of items. Depending on where loads of that type appear in the sequence of items, a reasonable estimation can be made of construction floor progress.

Step 908 may involve reporting construction floor progress to a site manager or other person by sending a message board alert to their mobile device, email accounts or through other mechanisms.

Step 304 and 904 will generally involve using machine learning to identify objects and loads and to determine their type - e.g. person, barrier, lifting frame, concrete bucket and so on. Presently, CentreNet was trained to detect key points, objects and loads and to determine the type of the objects and loads. Other methods such as Faster RCNN and SSD may also be used. The detection models may be trained using supervised learning. The data used in supervised learning may be taken from the site on which the system is intended to be used, or from multiple sites. The data may also be taken in various weather conditions to reduce the impact of noise caused by weather and disruptions to the images acquired by the image capture device.

The method 900 can also be used to track particular loads in the time they have been suspended e.g. by a tower crane as shown in Figure 10. In particular, since load being lifted onto side are detected at Step 904, a timer may be initiated for each lifted load per Step 910, the timer tracking a time for which the respective load has been lifted - i.e. the period of time between the first detected and either the current time or the time at which the load was deposited on the construction site, whichever occurs sooner.

A report may be made per Step 908 if the load is been hanging for longer than a threshold period, as detected by the timer. This requires Step 904 to continue monitoring the location of the load and its condition - i.e. elevated or deposited. The report may include raising alert 912 the load has been suspended for a particularly long period.

In each of the above methods 300 and 900, the statistics report may be sent to the construction manager or other person. Statistics report may include statistics such as the average number of breaches of social distancing measures statistics on the occurrence or re-occurrence of hazards and statistics on the average lift time of loads or of loads of a particular type before those loads are deposited on the construction site.

It will be appreciated that many further modifications and permutations of various aspects of the described embodiments are possible. Accordingly, the described aspects are intended to embrace all such alterations, modifications, combinations and variations that fall within the spirit and scope of the appended claims, including combinations of those claims. Throughout this specification and the statements or claims that follow, unless the context requires otherwise, the word "comprise", and variations such as "comprises" and "comprising", will be understood to imply the inclusion of a stated integer or step or group of integers or steps but not the exclusion of any other integer or step or group of integers or steps.

The reference in this specification to any prior publication (or information derived from it), or to any matter which is known, is not, and should not be taken as an acknowledgment or admission or any form of suggestion that that prior publication (or information derived from it) or known matter forms part of the common general knowledge in the field of endeavour to which this specification relates.