Art sector observers are disturbed by the risks inherent in what currently seem to be frenetic levels of activity
With every technological advance that can
benefit 
museum management comes another
that may 
assist thieves 

When protecting art treasures, the first instinct for many security professionals may well be to look at recent advances in technology. Hasn’t the advent of IP-addressable devices provided sufficient tools to protect art exhibits from theft in a discreet manner? Apparently not, and entrenched attitudes abound among curators. Consultants who so much as mention RFID tagging in a museum environment often receive sarcastic responses reminding them that they have been asked to secure works of art – not pets or livestock.

There has, however, been a gradual acceptance of RFID in the art world, particularly if the tag is small enough to occupy only the head portion of the frame of a painting and not extend to the back. But it’s unusual for museum RFID tags to have GPS tracking, and they are rarely monitored beyond a distance of 70 yards. There is no downloadable “Where’s My Painting?” app on Android or iOS. Furthermore, RFID tagging of a frame provides no protection against thieves who are willing to take a blade to the canvas.

An application where RFID tagging and GPS come into their own is when items are sent on loan to other galleries and a traveling case is placed around the regular frame. The Kröller-Müller Museum in the Netherlands (known for its van Gogh collection) has recently adopted this technique. But even with such technology in place, art sector observers are disturbed by the risks inherent in what currently seem to be frenetic levels of activity, with galleries lending each other works as part of “inter-museum horse-trading.”

Motion Detection

The video analytics lobby might point to the increasing reliability of intelligent scene analysis, but a confident thief placing a small painting in a shopping bag is not an easy scenario for an algorithm, and many types of legitimate behavior near a painting can cause nuisance alarms. By contrast (even as a small source of comfort) it should be noted that removing an oil painting from its frame is not an easy matter and in this context “canvas” in the sense of cloth is a misnomer. Centuries-old lacquer makes many canvases as stiff as a board, and simple motion detection within a CCTV camera let alone analytics is likely to expose the hacking and sawing movements needed to cut away a painting.

Simple motion detection within a CCTV camera let alone analytics is likely to expose the hacking and sawing movements needed to cut away a painting

Passive Infrared Sensor Advantages

Passive infrared sensors (PIRs) have been the mainstay of protection at galleries since the 1950s and continue to be a vital tool, although ceiling height can be a limiting factor. The usual technique is to create a 4-inch deep “wall” in front of the painting by projecting downward from a ceiling-mounted detector. It was after leaning in to one of these “curtains” once too often at my favorite portrait gallery that I was finally persuaded to buy a pair of bi-focal glasses. I had been performing an elaborate ritual whereby I would come within inches of a work in order to read the information panel and then back off in order to view the whole painting. By this time an alarm had sounded or a visual alert unseen by me had attracted a guard. This odd to-ing and fro-ing among the middle-aged has been practiced by and named after one of Britain’s foremost playwrights; it’s known as “the Alan Bennett minuet.”

Steven Keller of Florida-based Architect’s Security Group is a consultant whose expertise includes museum protection. He argues that, ideally, an infrared curtain should be combined with a low railing in front of pictures projecting out some three feet. This will allow responsible visitors to lean over if necessary for a better view or perhaps to indicate a detail to a companion or student without setting off an alert. The infrared field can then be tight to the picture and nuisance alarms from legitimate visitor activity will be minimised.

A veteran of numerous gallery and museum installation projects, Keller makes the point that unless the wall being protected by an infrared alarm is very long – longer than the range of the detector – then the field of coverage will project into walkways or other areas where surveillance is not required. This difficulty can be solved by using two opposing detectors and wiring the devices so they must both trip before an alarm is generated, or terminating the detector into the wall before it extends beyond the desired area.

Galleries are beginning to adopt a technology that in no way compromises the safety of exhibits or visitor experience
Passive infrared sensors (PIRs) have been
the 
mainstay of protection at galleries since the
1950s 
and continue to be a vital tool 

Analytics Better Than Infrared?

If a museum has suitable cameras then video analytics can become a viable alternative to projecting infrared beams in front of pictures. Areas that are prone to nuisance alarms can be masked off, and adaptive learning analytics can be “taught” that certain types of stimuli are not an attempt to steal the item but part of legitimate ambient activity.

Analytics can benefit museum curators more than infrared in so far as it may be possible to sound an alarm as soon as a sterile zone is compromised and prevent an incident whereas infrared will always be after the fact.

Access Control For Museum Security

Access control has much to offer museums and, far from ignoring developments in this sector, galleries are beginning to adopt a technology that in no way compromises the safety of exhibits or visitor experience. It should be remembered that many of the access challenges presented to museum managers are in areas not seen by the public. MIFARE cards that can be deactivated at will must have solved many headaches for security directors worried that a former member of staff may pose a threat. Similarly, electronic key management (often using RFID) where traditional keys are issued on a hierarchical “right-to-have” basis creates accountability and protects paintings when they are in vulnerable locations such as a restoration studio. (Stringent access control for staff may have prevented many incidents: the FBI currently estimates that 80 percent of art crime is committed with the aid of an insider.)

Passive infrared is primarily useful in protecting exhibits from the clumsy or over-curious but it also deters thieves. A strategy intended specifically to defeat the art thief is a small wireless transmitter placed at the back of a painting and connected to an impact sensor. Unless they are exceptionally dexterous, anybody removing the painting from the wall will send a signal to an alarm panel in a control room, an off-site alarm receiving center (ARC) or even to a smartphone app. These devices are of course reliant on a power supply in the control room and it would be interesting to know how many major art galleries have a back-up generator and how many take precautions against the possibility of thieves with electrical knowledge disabling entire power systems.

Saturation motion detection is
preferable to perfect perimeter
protection since museum thefts
can more easily occur by staying
behind than by breaking in

Sadly, with every technological advance that can benefit museum management comes another that may assist thieves. (I can hardly be the first person to have looked at the roofs and perimeters of London’s art galleries on Google Earth.) The sheer volume of current security innovations must however be favouring the good guys; video management systems (VMS) companies are not only allowing motion sensors or video analytics to trigger recording but they can also program their software to send clips (playable on a tablet or smartphone) to staff who are either off-site or elsewhere in a large building.

Understanding Perimeter Protection And Motion Detection

Perimeter protection manufacturers have much to offer the art sector. Nobody wants a museum to look like a fortress and many of the buildings are listed architecture whose façades cannot be compromised, but buried volumetric intruder detection is contributing to the security of numerous galleries. However, Steven Keller notes that perimeter protection provides no safeguard against the “stay behind” or against perhaps the most potent threat of all, the disaffected current or recent employee lurking in the building as was the case when ‘The Mona Lisa’ was stolen from the Louvre in 1911.

Keller says: “So many security designers, faced with a moderate budget, saturate galleries with motion detection rather than alarming every air intake vent in the room. While the intruder might not be immediately detected, he would eventually be apparent upon arrival in the collection-bearing area. Saturation motion detection is preferable to perfect perimeter protection since museum thefts can more easily occur by staying behind than by breaking in.” Keller is also at pains to stress that guards must also remain vigilant out of hours, and any security installation should be walk-tested every day at closing time in order to check functionality and flush out a “stay behind,” however remote this possibility may seem.

Share with LinkedIn Share with Twitter Share with Facebook Share with Facebook
Download PDF version Download PDF version

Author profile

Jeremy Malies European Correspondent, SourceSecurity.com

Jeremy Malies is a veteran marketeer and writer specializing in the physical security sector which he has covered for 20 years. He has specific interests in video analytics, video management, perimeter intrusion and access control.

In case you missed it

Disruptive Innovation Providing New Opportunities In Smart Cities
Disruptive Innovation Providing New Opportunities In Smart Cities

Growth is accelerating in the smart cities market, which will quadruple in the next four years based on 2020 numbers. Top priorities are resilient energy and infrastructure projects, followed by data-driven public safety and intelligent transportation. Innovation in smart cities will come from the continual maturation of relevant technologies such as artificial intelligence (AI), the Internet of Things (IoT), fifth-generation telecommunications (5G) and edge-to-cloud networking. AI and computer vision (video analytics) are driving challenges in security and safety, in particular, with video management systems (VMSs) capturing video streams and exposing them to various AI analytics. Adoption of disruptive technologies “Cities are entering the critical part of the adoption curve,” said Kasia Hanson, Global Director, Partner Sales, IOT Video, Safe Cities, Intel Corp. “They are beginning to cross the chasm to realize their smart city vision. Cities are taking notice and have new incentives to push harder than before. They are in a better position to innovate.” “Safety and security were already important market drivers responsible for adoption of AI, computer vision and edge computing scenarios,” commented Hanson, in a presentation at the Milestone Integration Platform Symposium (MIPS) 2021. She added: “2020 was an inflection point when technology and the market were ripe for disruption. COVID has accelerated the adoption of disruptive technologies in ways we could not have predicted last year.” Challenges faced by cities Spending in the European Union on public order and safety alone stood at 1.7% of GDP in 2018 Providing wide-ranging services is an expanding need in cities of all sizes. There are currently 33 megacities globally with populations over 10 million. There are also another 4,000 cities with populations over 100,000 inhabitants. Challenges for all cities include improving public health and safety, addressing environmental pressures, enabling mobility, improving quality of life, promoting economic competitiveness, and reducing costs. Spending in the European Union on public order and safety alone stood at 1.7% of GDP in 2018. Other challenges include air quality – 80% of those living in urban areas are exposed to air quality levels that exceed World Health Organization (WHO) limits. Highlighting mobility concerns is an eye-opening statistic from Los Angeles in 2017: Residents spent an average of 102 hours sitting in traffic. Smart technology “The Smart City of Today can enable rich and diverse use cases,” says Hanson. Examples include AI-enabled traffic signals to help reduce air pollution, and machine learning for public safety such as real-time visualization and emergency response. Public safety use cases include smart and connected outdoor lighting, smart buildings, crime prevention, video wearables for field agents, smart kiosks, and detection of noise level, glass breaks, and gunshots. Smart technology will make indoor spaces safer by controlling access to a building with keyless and touchless entry. In the age of COVID, systems can also detect face mask compliance, screen for fever, and ensure physical distancing. 2020 was an inflection point when technology and the smart cities market were ripe for disruption, Kasia Hanson told the MIPS 2021 audience. Video solutions Video workloads will provide core capabilities as entertainment venues reopen after the pandemic. When audiences attend an event at a city stadium, deep learning and AI capabilities analyze customer behaviors to create new routes, pathways, signage and to optimize cleaning operations. Personalized digital experiences will add to the overall entertainment value. In the public safety arena, video enables core capabilities such as protection of people, assets, and property, emergency response, and real-time visualization, and increased situational awareness. Video also provides intelligent incident management, better operational efficiency, and faster information sharing and collaboration. Smart video strategy Intel and Milestone provide video solutions across many use cases, including safety and security Video at the edge is a key element in end-to-end solutions. Transforming data from various point solutions into insights is complicated, time-consuming, and costly. Cities and public venues are looking for hardware, software, and industry expertise to provide the right mix of performance, capabilities, and cost-effectiveness. Intel’s smart video strategy focuses around its OpenVINO toolkit. OpenVINO, which is short for Open Visual Inference and Neural network Optimization, enables customers to build and deploy high-performing computer vision and deep learning inference applications. Intel and Milestone partnership – Video solutions “Our customers are asking for choice and flexibility at the edge, on-premises and in the cloud,” said Hansen in her presentation at the virtual conference. “They want the choice to integrate with large-scale software packages to speed deployment and ensure consistency over time. They need to be able to scale computer vision. Resolutions are increasing alongside growth in sensor installations themselves. They have to be able to accommodate that volume, no matter what causes it to grow.” As partners, Intel and Milestone provide video solutions across many use cases, including safety and security. In effect, the partnership combines Intel’s portfolio of video, computer vision, inferencing, and AI capabilities with Milestone’s video management software and community of analytics partners. Given its complex needs, the smart cities market is particularly inviting for these technologies.

What Are the Physical Security Challenges of Smart Cities?
What Are the Physical Security Challenges of Smart Cities?

The emergence of smart cities provides real-world evidence of the vast capabilities of the Internet of Things (IoT). Urban areas today can deploy a variety of IoT sensors to collect data that is then analyzed to provide insights to drive better decision-making and ultimately to make modern cities more livable. Safety and security are an important aspect of smart cities, and the capabilities that drive smarter cities also enable technologies that make them safer. We asked this week’s Expert Panel Roundtable: What are the physical security challenges of smart cities?

New Markets For AI-Powered Smart Cameras In 2021
New Markets For AI-Powered Smart Cameras In 2021

Organizations faced a number of unforeseen challenges in nearly every business sector throughout 2020 – and continuing into 2021. Until now, businesses have been on the defensive, reacting to the shifting workforce and economic conditions, however, COVID-19 proved to be a catalyst for some to accelerate their long-term technology and digitalization plans. This is now giving decision-makers the chance to take a proactive approach to mitigate current and post-pandemic risks. These long-term technology solutions can be used for today’s new world of social distancing and face mask policies and flexibly repurposed for tomorrow’s renewed focus on efficiency and business optimization. For many, this emphasis on optimization will likely be precipitated by not only the resulting economic impacts of the pandemic but also the growing sophistication and maturity of technologies such as Artificial Intelligence (AI) and Machine Learning (ML), technologies that are coming of age just when they seem to be needed the most.COVID-19 proved to be a catalyst for some to accelerate their long-term technology and digitalization plans Combined with today’s cutting-edge computer vision capabilities, AI and ML have produced smart cameras that have enabled organizations to more easily implement and comply with new health and safety requirements. Smart cameras equipped with AI-enabled intelligent video analytic applications can also be used in a variety of use cases that take into account traditional security applications, as well as business or operational optimization, uses – all on a single camera. As the applications for video analytics become more and more mainstream - providing valuable insights to a variety of industries - 2021 will be a year to explore new areas of use for AI-powered cameras. Optimizing production workflows and product quality in agriculture Surveillance and monitoring technologies are offering value to industries such as agriculture by providing a cost-effective solution for monitoring of crops, business assets and optimizing production processes. As many in the agriculture sector seek to find new technologies to assist in reducing energy usage, as well as reduce the environmental strain of modern farming, they can find an unusual ally in smart surveillance. Some niche farming organizations are already implementing AI solutions to monitor crops for peak production freshness in order to reduce waste and increase product quality.  For users who face environmental threats, such as mold, parasites, or other insects, smart surveillance monitoring can assist in the early identification of these pests and notify proper personnel before damage has occurred. They can also monitor vast amounts of livestock in fields to ensure safety from predators or to identify if an animal is injured. Using video monitoring in the growing environment as well as along the supply chain can also prove valuable to large-scale agriculture production. Applications can track and manage inventory in real-time, improving knowledge of high-demand items and allowing for better supply chain planning, further reducing potential spoilage. Efficient monitoring in manufacturing and logistics New challenges have arisen in the transportation and logistics sector, with the industry experiencing global growth. While security and operational requirements are changing, smart surveillance offers an entirely new way to monitor and control the physical side of logistics, correcting problems that often go undetected by the human eye, but have a significant impact on the overall customer experience. Smart surveillance offers an entirely new way to monitor and control the physical side of logistics, correcting problems that often go undetected by the human eye. Video analytics can assist logistic service providers in successfully delivering the correct product to the right location and customer in its original condition, which normally requires the supply chain to be both secure and ultra-efficient. The latest camera technology and intelligent software algorithms can analyze footage directly on the camera – detecting a damaged package at the loading dock before it is loaded onto a truck for delivery. When shipments come in, smart cameras can also alert drivers of empty loading bays available for offloading or alert facility staff of potential blockages or hazards for incoming and outgoing vehicles that could delay delivery schedules planned down to the minute. For monitoring and detecting specific vehicles, computer vision in combination with video analysis enables security cameras to streamline access control measures with license plate recognition. Smart cameras equipped with this technology can identify incoming and outgoing trucks - ensuring that only authorized vehicles gain access to transfer points or warehouses. Enhance regulatory safety measures in industrial settings  Smart surveillance and AI-enabled applications can be used to ensure compliance with organizational or regulatory safety measures in industrial environments. Object detection apps can identify if employees are wearing proper safety gear, such as facial coverings, hard hats, or lifting belts. Similar to the prevention of break-ins and theft, cameras equipped with behavior detection can help to automatically recognize accidents at an early stage. For example, if a worker falls to the ground or is hit by a falling object, the system recognizes this as unusual behavior and reports it immediately. Going beyond employee safety is the ability to use this technology for vital preventative maintenance on machinery and structures. A camera can identify potential safety hazards, such as a loose cable causing sparks, potential wiring hazards, or even detect defects in raw materials. Other more subtle changes, such as gradual structural shifts/crack or increases in vibrations – ones that would take the human eye months or years to discover – are detectable by smart cameras trained to detect the first signs of mechanical deterioration that could potentially pose a physical safety risk to people or assets. Early recognition of fire and smoke is another use case where industrial decision-makers can find value. Conventional fire alarms are often difficult to properly mount in buildings or outdoor spaces and they require a lot of maintenance. Smart security cameras can be deployed in difficult or hard-to-reach areas. When equipped with fire detection applications, they can trigger notification far earlier than a conventional fire alarm – as well as reduce false alarms by distinguishing between smoke, fog, or other objects that trigger false alarms. By digitizing analog environments, whether a smoke detector or an analog pressure gauge, decision-makers will have access to a wealth of data for analysis that will enable them to optimize highly technical processes along different stages of manufacturing - as well as ensure employee safety and security of industrial assets and resources. Looking forward to the future of smart surveillance With the rise of automation in all three of these markets, from intelligent shelving systems in warehouses to autonomous-driving trucks, object detection for security threats, and the use of AI in monitoring agricultural crops and livestock, the overall demand for computer vision and video analytics will continue to grow. That is why now is the best time for decision-makers across a number of industries to examine their current infrastructure and determine if they are ready to make an investment in a sustainable, multi-use, and long-term security and business optimization solution.