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Understanding how Forklifts move throughout a warehouse has always been a need: knowing how forklifts move, how operators use them, can significantly improve the operations management and the productivity.
Having an overview of the movements and utilization patterns of forklifts can let you cut the business expenses by optimizing the operations.
Forklifts and Lifting Trucks are a necessary part of the manufacturing, transportation, and warehousing industries. Yet, many businesses only use them to a fraction of their maximum potential.
Knowing the location of forklifts and being able to track this data over time can lead to great improvements.
There are several technologies that promise to track forklifts in real time, claiming Real-Time updates with Active RTLS/RFID systems. Bluetooth/BLE, WiFi, Ultra Wide Band (UWB) and RFID have been used to track moving assets and people, but when it comes to forklifts tracking they are not the best options to choose from.
These technologies, based on radio frequency (RF), require the deployment and maintenance of an on-site infrastructure (“antennas”, “nodes”, “receivers”) throughout the warehouse that detect the presence of “Tags”, attached to the forklifts.
Not only the deployment is time consuming and expensive, but the final results are not even satisfactory. The average accuracy of BLE Tracking inside a warehouse, considering the open space and the amount of metallic surfaces creating interference, ranges between 5 and 8 meters: definitely not accurate enough for a Real-Time Locating System solution. Likewise, the other RF based technologies have significant accuracy and latency issues that cannot be overcome.
At Accuware we have a lot of experience with RF based location technologies: we developed WiFi and Bluetooth based tracking systems almost 10 years ago. We decided then, back in 2015, to focus our efforts on the development of a new technology able to address use cases that could not take advantage of radio frequency based systems.
In this context we created Dragonfly, our unique Visual SLAM (vSLAM) technology.
Dragonfly can provide centimeter accuracy using just an on-board camera. This technology does not require the deployment of “receivers” throughout the site, nor the installation of “antennas” or other fixed equipment. In addition, the precision is extremely high and the location is computed in real time, with a refresh rate up to 60 Hz (60 location updates per second).
A forklift location overview is important. The amount of data that you can collect from forklift tracking is tremendous and has a crucial importance for business analysis:
Dragonfly is used to collect data inside the warehouse and can be used to collect data outside the warehouse (sometimes in combination with a GPS unit). The possibilities of data collection related to forklifts are many:
We can also create custom analysis and reports, to let you analyze which operators finish the most orders and which operators get speed or pedestrian warnings, you can compare charts across the vehicle fleet (utilization, efficiency, accidents, average speed, average daily distance, etc.)
Speaking of cost, a large warehouse can have dozens of forklifts and similar vehicles operating at the same time on the floor.
A big fleet can have a significant impact on your budget: purchase or leasing of vehicles, maintenance, electricity for recharging, and the expense of extra workers to operate those vehicles are costs that businesses are constantly facing.
Implementing a Forklifts Tracking solution can help you control and reduce these costs:
Dragonfly allows managers to analyze vehicle usage with an aim towards improving efficiency. When you are better able to use your existing equipment, you may be able to reduce the amount of vehicles on the floor.
With a smart combination of hardware and software, Dragonfly provides the manager the ability to keep their fleet at high efficiency levels and save money.
Without a proper procedure in place, operators are forced to figure out the best routes to take across the floor on their own. This can lead to errors and accidents. Sometimes operators need to backtrack because of other vehicles, pedestrians, or even pallets that were in the way. This wasted time could be used to fill other orders.
With Dragonfly you can understand which are the most crowded routes, where operators have to backtrack often, where the most of the accidents happen, and plan the best routing model for the future.
Dragonfly is able to detect forklift and lifting truck speed and acceleration. This enables the possibility of configuring speed limits throughout the warehouse or inside specific areas and geo-fences. The operator can receive an alert when the speed is over the limit. In some cases it is also possible to configure the forklifts to limit their speed automatically and Accuware’s engineering team can design and develop the on-board controlling system.
Dragonfly also keeps a record of all the events and activities so that they can be reviewed and analyzed to improve operator efficiency and overall safety.
It is fundamental nowadays to stay updates and take advantage of technical innovations: technology is progressing faster than ever, bringing new possibilities to businesses to improve their operations and reduce the costs. Lacking or staying behind in technology can create competitive disadvantages and can lead to losses of contracts when clients prefer to assign their contracts to more advanced companies. Dragonfly is a RTLS that allows businesses to remain at the cutting edge of technology when it comes to forklifts tracking: it makes it possible to have:
Forklift tracking solutions can improve your business and significantly reduce the operational costs. Reduced accidents less wasted hours, and less unused vehicles mean more productivity and lower costs for maintenance and operations.
Dragonfly lets you be competitive in a sector that is continuously evolving and adopting new technologies and solutions for better operations.
If you want an advanced indoor location technology for your warehouse and if you would like the advice of our experts, do not hesitate to contact us.
At Accuware we can deliver the right technology for your requirements and we provide consulting services as well, for complete custom projects. Our team will be delighted to speak with you.
A new technology trend is emerging in the retail industry: robots and autonomous machines are being introduced to perform many tasks. The robots will substitute lower-level jobs, both in maintenance functions and basic inventory functions, in order to manage rising costs.
The world’s largest retailer, Walmart, is carrying thousands of robots on board in nearly 5,000 of its 11,348 stores. According to CNN Business, these robots will wash floors, scan boxes, unload trucks and track shelf inventory, primarily at domestic locations in the United States.
A new unloading robot has already been used at the docks of hundreds of stores, extracting boxes from delivery trucks while automatically scanning and sorting goods. The unloader will be used at more than 1,100 points of sale in the near future.
“Automating certain tasks,” according to Walmart CEO Doug McMillon “gives employees more time to do the work that satisfies them and to interact with customers. Following this logic, the retailer points to robots as a source of increased efficiency, increased sales and reduced employee turnover.
Tests in dozens of markets and hundreds of stores have shown the effectiveness of robots, but how can replacing people with machines really reduce employee turnover?
This statement remains to be seen, but there seems to be strong support for greater profitability through robotics.
“As we evolve, there are some jobs that will disappear,” said Michael Dastugue, Chief Financial Officer of Walmart in the United States. The message is clear: robots remain a valuable resource to replace low-level jobs. The company says that this investment will allow human workers to perform more varied tasks, as robots take jobs that humans don’t want to do anyway.
Walmart’s obligation to its people remains strong – if by “people” we mean “shareholders“.
Business considerations are at the center of the transition to the use of new technologies and employees will have to adapt. Consider these statistics in a recent study commissioned by Bossa Nova Robotics. (Full disclosure: Bossa Nova is the manufacturer of inventory evaluation robots at Walmart, and others. With more than $70 million in capital raised, this Carnegie-Mellon-driven venture is revolutionizing retail sales with robots, according to CNBC sources.)
Based on responses from 100 retail executives from companies with revenues over $500 million, 99% reported inventory problems. In addition, this survey showed that
Providing indoor location to robots is crucial when they need to autonomously move throughout a complex space. It is even more important if customers are walking throughout a supermarket while the robots move around the aisles.
Precise indoor location becomes a key component for robots: in GPS-denied environments, such as supermarkets and stores, it is necessary to consider alternative technologies for positioning.
At Accuware we have developed Dragonfly, a technology for robots and autonomous vehicles able to provide precise location using just computer vision. Our team has been working with several customers in retail to implement indoor location technologies, and Dragonfly is the state of the art system for similar applications.
Dragonfly is a Visual SLAM technology: unlike other systems, such as LiDARs, it does not require the installation and calibration on board of expensive hardware, nor the presence of multiple sensors for “sensor fusion” computations. Dragonfly simply requires a camera on board and uses the video stream to compute the real time location of the robot: this data can be fed it to the navigation and piloting system.
If you need an advanced indoor location technology for your project, or if you would like the advice of our experts, do not hesitate to contact us.
At Accuware we can deliver the right technology for your requirements and we provide consulting services as well, for completely custom projects. Our team will be delighted to speak with you.
One of the main problems of Retail Stores is to measure traffic and understand how people move throughout the space.
In this context, some of our customers have decided to use our innovative Intelligent Video Tracking technology, Sentinel.
Sentinel is a computer vision technology that uses Artificial Intelligence to process videos from existing Video Cameras (CCTV cameras) installed in the venue. Sentinel is able to detect and identify people: it can be used to track the presence of people, analyze footfall, and collect the precise location of each customer.
One of our clients, Modani, in Miami, Florida, has been one of the first customers to use Sentinel to monitor the location and presence of customers, and track their behavior inside the store.
Modani has installed multiple cameras throughout the store to measure the traffic and analyze the movements of customers.
Modani Furniture is a worldwide famous brand for high-end modern and contemporary furniture. Modani focuses on simple geometric shapes rather than the heavy ornamentation typically found in traditional or contemporary furnishings.
Each piece of furniture is designed to be personal: Modani sources beautiful materials from around the world, such as raw-edge acacia wood, stainless steel, nickel or aluminum, velvet, suede, and silk to create furniture profiles that are transitional.
Modani has several stores across the United States and their Miami retail space has been equipped with Sentinel video tracking for several years.
The first and main advantage of using retail analytics is that they provide tangible and actionable insights about customers’ behavior.
Handling the aspects of a business becomes way easier when one knows how to measure the return on investment. Retail analytics makes it possible. Retail analytics gives a highly accurate picture to retailers of what works and what doesn’t: this becomes crucial when trying to understand the customers’ response to a product or to a marketing campaign.
As mentioned above, retail analytics helps in measuring the return on investment (ROI) across various aspects of business management.
Therefore, Analytics can have a deep impact on enhancing the ROI from marketing endeavors. A store manager can measure the effect of in-store influences and modifications on purchase patterns, so he can alter future campaigns accordingly.
He can focus on effective campaigns and plan marketing initiatives based on what triggers specific customers’ actions.
In-store analytics offer a strong understanding of the consumer behavior. Tracking the shopping patterns and analyzing dwell times can reveal several opportunities for all types of retail operations, from individual stores to large shopping malls. Managers can change the layout to be more attractive, can plan the service delivery quality that customers like the most and the product placements that draw maximum attention.
With these KPI at hand, retailers can manage the best staffing options, the most attractive design techniques and the best selling tactics, based on real data.
Retail analytics helps in understanding the relationship between a store and its visitors, by giving useful insights into customer behavior.
It helps the retailer to get the right information across to the desired recipient and ensure a nice shopping experience for the buyer. By personalizing marketing content based on the customers’ response, retailers are able to showcase the relevant products and offers to the most responsive audience, therefore increasing the propensity in them to buy.
This also increases the brand perception with the customers who feel valued. As a consequence, this positively affects the loyalty that they feel towards the brand.
Retail analytics plays a crucial role in improving the efficiencies in daily business management.
Predictions based on analytics let the retailer take immediate actions for decision-making on stocking, tracking, and restocking SKUs on a convenient and regular basis. Keeping a track of how often a particular product is sold, sellers can predict and analyze the trends that are dominant in the current market. This insight can help identify the most popular items, concentrating on these and similar products to improve the lateral sales.
Modani has installed several CCTV cameras to use Accuware Sentinel: Sentinel is an intelligent video tracking system that enables all kinds of retail analytics.
Sentinel makes it possible to build solutions and software to analyze visitors’ behavior by following the movements of people inside venues and stores, identifying and tracking them by their visual appearance.
Sentinel provides API and raw CSV files that can be integrated into analytic systems, and Accuware’s partners can also deliver an end-user application for retail analytics, if required.
Upload your video on our demo page and get it processed by Sentinel!
Accuware Dragonfly, a visual SLAM technology based on computer vision, provides accurate location to robots, drones, machines and vehicles. But, what is SLAM? How does it work?
This article wants to give a brief introduction to what SLAM is, how it works, what it’s for (and what it’s not for), and why it is important for the new industry revolution.
The importance of Simultaneous Localization and Mapping (SLAM) is constantly increasing, not only among the computer vision community, but across multiple industries. It is receiving specific interest from augmented and virtual reality industries, and from the robotics and automation sector.
SLAM is in fact now able to address localization problems that many industries have been facing along the years.
There is however large variety of SLAM systems available, from the academic world and from the industry: in this context, and to clarify the typical confusion around this new technology, it is worth exploring what SLAM means and how it works.
What is SLAM?
‘SLAM’ does not refer to a particular algorithm or specific software: it rather refers to the problem of simultaneously localisation (know the location/position and orientation) of a device with respect to its surroundings and at the same time create a map of the environment.
SLAM can be done in a number of different ways: SLAM is not strictly a computer vision topic, and it could also work with other technologies, such as lasers scanners and LiDARS.However, in this article, we will focus on visual SLAM, which is the most innovative technology. In fact, at Accuware, we have decided to focus on the development of Dragonfly, our visual SLAM system, to offer a valid alternative to other SLAM technologies that rely on specific hardware, such as LiDARs, and to create a brand new positioning algorithm.
Computing both the position of the device and the map, through the on-board camera, when neither are known, distinguishes the SLAM problem from other technologies.
For example, 3D mapping/reconstruction with a fixed camera rig is not SLAM, because while the map is being recovered, the positions of the cameras are already known and fixed. SLAM instead provides the ability to recover both device’s pose and the map structure, initially knowing neither of them.
It is important to note that this if one of the key features of SLAM: computing the pose creating the map in real time is in fact what makes SLAM different from other systems. This also means that the processing is typically “on the fly” so that the camera’s location is continuously known and updated.
Dragonfly, however, is able to also post-process existing videos: this is extremely useful in order to improve the accuracy inside some challenging environments, and to perform preliminary tests to estimate the final accuracy of the system, without being on site.
A Brief History of SLAM
The first researches on SLAM began among the robotics community: 1986 papers by Smith and Cheeseman are usually indicated as the first technical documents about SLAM, originally applied to wheeled robots on a flat ground. The first SLAM systems were combining different sensor readings (laser scanner or sonar, for example) with data from the control input (steering angle) and mechanical measurements (such as wheel rotations counts).
In recent years, instead, visual sensors have become a crucial aspect of SLAM research: the improvement of computer vision techniques and the high computation power of processors are opening a new era for SLAM.
Many studies on visual SLAM focused on the use of stereo cameras, or cameras in combination with other sensors (“sensor fusion”).
At Accuware we have decided instead to explore the pure computer vision SLAM, using only monocular cameras, without external sensors. While Stereo Cameras can be used with Accuware Dragonfly, they are not required.
Our scope has been to make SLAM a widely useful technology that does not require additional hardware or sensors. We wanted to deliver a precise location system based on visual information that can be derived from an existing on-board camera, removing the need of sensor fusion and of other hardware to be mounted on board of robots and drones.
How SLAM Works
Dragonfly analyzes the video stream coming from the device’s camera: it keep tracks of a set of points (“features”) through multiple camera frames and uses them to triangulate the 3D location of the device and create a virtual map of the environment. At the same time, Dragonfly can use the estimated point locations to calculate the camera’s pose.
With the use of a single monocular camera, carefully merging the different features detected over multiple frames, Dragonfly can elaborate the pose of the device (6-DOF) and map the structure of the surrounding ambient with high accuracy, up to an accuracy of 5 cm.
Dragonfly also includes the ability to improve the map quality over time, to increase the accuracy, and leverages loop closure: this automated procedure makes it possible to reduce the gradual accumulation of errors over time. The current location computed by Dragonfly can be associated to a preliminary known location inside the map (Visual or Virtual Markers), optimizing the map structure and reducing the accumulated error.
The map is then used to perform relocalisation: if the device experience a low tracking performance, which can lead to the system getting “lost”, Dragonfly is able to recognize a previously detected “feature” and use it as a marker to compute the relative location inside the map.
Relocalisation is also useful to start the positioning of the device from any place inside an existing map: the starting point is automatically recognized by Dragonfly, analyzing and recognizing the surrounding features.
SLAM in Real Applications
Now that we know how SLAM works, how can this system be useful in real life? How can Dragonfly be applied to actual projects?
Visual SLAM is nowadays needed in many different applications.
Dragonfly is used to remotely track the location of moving vehicles, such as forklifts, inside large environments. Dragonfly’s ability to dynamically update the map is extremely important in similar venues, which are subject to constant changes. Some of our customers are leveraging Dragonfly to monitor the usage of machines and ground robots (think about industrial cleaning machines, lawn mowers…), and others have been installing Dragonfly on board of flying drones to improve some operations inside GPS denied environments, such as inventory management.
We work with customers that have been developing self-driving robots and vehicles, and who are exploring autonomous navigation for drones as well.
In the era of automation, with the roll out of unmanned vehicles and with the beginning of commercial drones’ applications, Dragonfly is becoming an essential technology to provide positioning where GPS is not an option and where centimeter accuracy is necessary.
Ecsite, the international non-profit whose name is the acronym of European Collaborative for Science, Industry and Technology Exhibitions, has been an event since its founding in the early 1990’s. Bringing together a European network of science centers and museums, its vision is to foster creativity and critical thinking in European society, encouraging citizens to engage with science. Ecsite’s history provides a fascinating glimpse into the evolution of an institution whose mission is to inspire organizations that engage people with science, not just in Europe, but also worldwide.
Our partners at Wezit attended Ecsite 2018, which was held at the Natural History Museum of Geneva, Switzerland, June 7 through 9. Wezit’s Ségolène Valençot shared with us some vignettes of various gatherings she attended. These are her postcards from this event.
We are still on an #Ecsite cloud mode! This year’s conference took place in the beautiful city of Geneva, during the first days of June. Perfect weather, the air was filled with the energy and the great ambiance of 1,182 professionals from 58 countries, all gathered for three days to reinvent how we communicate, teach, learn, and think! After all…no wonder why this year’s theme was Creative collisions!
Wezit attended the Recontextualizing Collections panel; the speakers presented real case scenarios on how museums and their collections can increase the contact with their audiences.
First, we listened to Maria João Fonseca, the Interim Executive Coordinator of the Natural History and Science Museum of the University of Porto, who shared with us how they made a priority to engage their visitors. Thus by creating stories within stories, museums within museums, using the documentation available in the collections. For example, by interpreting the 1930’s dreamy Portuguese poets, displays are used to showcase the Whale skeleton at the Museum of Porto Gallery.
A particular thought to the idea of museums within museums was taken by a scenography incorporating Cabinets of Curiosities dating from the 19th and the beginning of the 20th century. Touching the visitors’ emotions, moving their curiosity, attracting them by using a mix of stories, as well as history and literature – the idea was to give life to objects and ultimately use them as a learning tool!
Lastly, Fonseca explained how important it is to evaluate how visitors experience and understand these museography proposals and scenographies.
Starting from more or less the same principle of the “museum within museums” idea, Beat Hächler, Director of the Swiss Alpine Museum at Bern, Switzerland, gave us his insights on “museum intimacy”. He talked to us about dropping the permanent exhibition principle and go for a kind of mini-exhibiting units, such as pop-up schemes or event venues. Moreover, he emphasized the needs of creating unique spaces that help visitors to connect to the collections, those museum objects surprising them by finding out about things they never knew about the collection – as if the exhibit and the visitor were in a conversation and they shared their stories.
Bringing visitors closer to the museum and making it more available to them by revealing the “behind the scenes” aspects of the collection and its motivations, is also a priority for Grégoire Mayer, co-director at the Musée d’Ethnographie Neuchâtel.
And if you enjoyed Shawn Levy and Chris Columbus’ film “A night in the museum”… then you will agree with Hervé Groscaree, from the Natural History Museum of Geneva, and invite visitors to sleep and do overnight museum activities , move with visitors in the nature and feel authentic experiences in relation with the collections of the Museum!
Even though it does not compare the size and magnitude of a museum, if you ever went through a home or office renovation while still living at your place, you would relate to this session and be open to learn and listen about what the speakers & participants have to share!
Every once in a while, every museum, science center – no matter their size, will eventually go through a renovation. Not only construction-wise, but also concerning the updating of their presentation techniques.
Some institutions will opt to open their doors while going through these improvements; others will temporarily close, others will make key pieces of their collection available to visitors, such is the case of the Musée Lorrain. Wezit completed tactile digital tables showcasing key pieces of their collection, while the museum’s temporary closure, and those are available online for visitors to admire until they reopen their doors.
As part of a constant search to understand the challenges museums and institutions go through, we attended the Balancing construction works and visitor satisfaction Conference at the #Ecsite2018 conference. In this cooperative gathering, speakers share their experiences, strategies and results, adaptable to smaller and to significant bigger organizations.
Speakers from centers located in Amsterdam, Belgium and Germany, pointed out in a TO DO LIST presentation general tips, ideas ranging from financial planning, visitor communication as well as content development.
The real case scenarios presented included the following museums, which were there as participants to this session:
The Jaermuseet in Norway: They mastered in getting feedback from their visitors with customizable surveys, and open-ended questionnaires.
The Jaermuseet obtained an average of 80% responses from families and teachers. The results had a satisfactory rate, which motivated the staff, and uncovers ways to improve. Moreover, surveys referring to open and recreational spaces echoed the museum’s presentation and how it is perceived by its visitors. Overall the Jaermusset focused their visitors as the best museum’s ambassadors!
On the other hand, more interesting real case examples discussed were: The Eureka Science Center which has been conducting visitors analysis since the 1980’s, enabling them to have a good knowledge of what they offer in their cultural and scientific presentation.
Visitors identify the Center as a place to do family activities; furthermore, the tracking of their visitors’ behavior from the moment they buy their ticket online for the duration of the tour, and lastly the rise of the website and social media as a medium to obtain what motivates and interests their audience.
Maarten Okkersen talked to us about the Internet component in the museum sphere and the power of blogging moms that follow the museum’s latest happenings. How they can be a good pairing with these institutions, which leads to the importance of knowing the basic of SEO and the interpretation of google analytics.
Furthermore, how it can attract those that are considered visitors and non-visitors, hence, the museum becomes not only a cultural place but also perceived a place of fun and entertainment.
Finally, the Copernicus Center in Warsaw shared their views on balancing between data and intuitions.. Now you should be in route towards your institution’s customer satisfaction journey!
At Accuware, we love Wezit. Their innovation and creativity shine through in every project they touch. Since our first collaboration, supporting indoor navigation on their Ma Visite app with Accuware location technology at the Nantes Museum of Art, there has been great synergy between us.
Having Wezit share what they learn at industry-specific gatherings like Ecsite, often helps us visualize potential new applications of our technologies, to implement solutions that address their challenges.
Wezit’s people are true innovators in many creative ways, always focused on educational institutions. At Accuware, the location technology providers, we look forward to a long term collaboration for many years to come.
As we know, urban planning concerns itself with the design and regulation of the uses of space in the urban environment, and on the location of human activities within it. Regarding existing urban settings, a key concern is understanding how the space is currently used, and how it would be affected by change, both from redesign, or simply from increased use over time.
This story, shared by Senior Transport Consultant Francesco Angelelli, highlights how Atkins, a leading international consulting company, used an innovative approach leveraging the latest technologies to study human behavior and use patterns at an iconic place: Oxford Street in the City of Westminster, one of the most famous destinations in London.
Originally part of the Via Trinobantina, a Roman road between Essex and Hampshire, Oxford Street has existed for over 2,000 years. It became Oxford Street in the 18th century, when it began to change from residential to commercial. Today, it is Europe’s busiest shopping street, with half a million daily visitors.
Because of its popularity among tourists and shoppers, the street’s capacity is under increasing pressure. Businesses compete to secure a high-profile presence in the area. As a result, there are growing concerns about traffic pollution, general accessibility and pedestrian safety. In addition, the opening of the Elizabeth Line, the railway route built by Crossrail, under construction since 2009, due to open in December 2018, is expected to increase footfall and exacerbate existing problems. All of this has prompted a much needed discussion about the need to reshape the area’s public use.
The Crown Estate appointed a multi-disciplinary team to develop proposals for Oxford Circus and its surrounding streets. Atkins’ pedestrian modeling team was involved in the proposal’s assessment to accommodate the increased demand, improving accessibility while providing visitors with a world-class experience.
Key project challenges were the size of the area to be assessed and the large number of pedestrians involved. Developing a model capable of simulating existing conditions in such an environment demanded innovative data collection methods supported by traditional survey data. After evaluating several survey technologies, the Atkins team opted for WiFi Survey: monitoring the movement of active WiFi- enabled devices throughout the study area. WiFi survey provides relatively clean samples with high sample rates. In addition, it enables relatively straightforward long-term comparison between different monitored areas, which would be difficult, if not impossible using traditional sampling methods.
Following their standard approach, the Atkins team developed a base-year model which simulates existing conditions to a reasonable level of validation. The methodology has been successful in the calibration of the base model (R-Squared of above 0.96 and GEH < 5 for most measured flows). They used this as a basis for the development of future year scenarios for the assessment of design alternatives. The 2018 demand level has also been increased to develop 2019 models.
All models were rendered in a 3D Virtual Reality environment, so the team could literally experience walking through the base model. This proved to be an incredibly useful aid in refining and visually validating modeling assumptions, thus solving a common problem in the pedestrian modeling sector, as standard software only allows modelers to visualize simulated crowds from a distance. The 3D Virtual Reality environment also enabled exploring spatial improvements with the design team in a seamless and highly effective manner.
The Atkins team deployed 21 WiFi devices (“nodes”) on building cornices. The nodes were attached to the building’s floodlight mains and used 3G/4G connections to stream data in real-time. Behind the scenes, Accuware’s WiFi Location Monitor system determined the approximate location of all WiFi devices by triangulating their positions based on their signal strength.
One day, August 11th at 9 AM, the number of devices detected peaked and then suddenly dropped. As this trend was very unusual for this time of the day, the team worried that the system was experiencing technical problems. But just then they learned that Oxford Circus station had been evacuated because of a train on fire. With the station temporarily out of service, the overall population in the area was lower than usual. This incident revealed that the data captured will be very useful for planning emergency operations.
As the datasets were growing week by week, the team began analyzing the data and obtaining useful insights both for modeling and for stakeholder information. For example, the combination of Origin-Destination (O/D) matrices and daily profiles for both weekdays and weekends enabled them to define different areas by showing which were commuter-driven, leisure-driven, and neutral; where neutral is the configuration that maximizes public space usage throughout the week, an important indicator of the quality of public spaces.
The analysis covered sample speeds on Argyll Street, which is a pedestrian lane, and Regent St which is not. As the speed profiles are similar it is clear that the data was not influenced by vehicular traffic. However, for some devices the detected distance is less than the actual one due to low reporting frequency. The team expected that the resulting average speed would be overestimated. To eliminate this effect, they did not consider higher (and implausible) values. When the tails were excluded, the profiles show a normal distribution with an average speed of 1.2 meters/sec.
To implement their solution, the Atkins team deployed Accuware’s WiFi Location Monitor, a system designed to passively detect and locate active WiFi devices, such as cell phones and tablets.
Using WiFi Location Monitor requires deploying WiFi “nodes“, which are WiFi routers set on listening mode. Nodes detect the presence and signal strength of active WiFi devices nearby, uploading their data to a cloud-based server. The server estimates the location of each WiFi device from the signals collected by multiple nodes. Each device is identified by its WiFi MAC address. Note that no personally identifiable information is ever collected. All collected data is truly anonymous. Actual location of each device is estimated within a 3-meter radius of its actual location. which is ideal for urban use surveys.