Neil Killick, regional manager (Northern Europe) at Milestone discusses how artificial intelligence, data and increasingly powerful VMS will transform our cities’ safety.
Using increasingly sophisticated technology to keep our cities safe and running smoothly is now a daily reality, thanks to advances in artificial intelligence (AI), machine learning, data, cloud computing, and powerful video management systems (VMS).
Technology is quickly leapfrogging criminals, transforming the way police gather evidence, carry out forensics and combat crime. Simultaneously, advanced data analysis and video systems are helping to keep our streets safe. To forewarn of pedestrian dangers, for example, heatmap movements through a public space and monitor public transport for dangerous situations.
Embedding technology throughout our cities is making them smart. And smart cities are, ultimately, safer cities. Using the insights from such technology, city planners can create safer cityscapes, police and security personnel can hone in on crime and everyone feels more secure as a result.
Navigating the safe city
But what exactly is a safe city? First and foremost, safe cities involve collaboration. To keep an entire city secure, you must have systems that integrate and speak to each other, a shared infrastructure, sensors connected to a common network and multi-agency buy-in. Without these things, your safe city programme will be stuck in a silo.
Organisations must work together towards the shared goal of citizen safety. On a granular level, this involves knowing the processes for sharing information, key stakeholders, who takes direction from whom and crisis communication procedures.
The building blocks of a safe city
You need real-time information from traffic systems, the Internet of Things (IoT), resource locations, video systems, weather and other intelligence. Insights can be found in every corner of a safe city. Especially via the power of video. Video data and analytics can combine with an array of IoT sensors and databases to offer real-time updates and crime predictions.
Keeping on top of the masses of data and video feeds is an impossible task for a human. Therefore, safe cities also have a significant amount of automation. Computers can analyse historical security footage to gain a baseline understanding of ‘normal’ behaviour. When real-time footage deviates from the norm, an alert can be issued and a human team can step in to react.
Improving public safety
This doesn’t just have applications for predicting or recognising a crime. It also improves public safety when, for instance, an individual has had one too many on a Saturday night. Or if someone poses a suicide risk.
Video cameras in a train station could capture a pedestrian who suddenly falls onto the tracks. This information can be relayed back to an advanced VMS that alerts the station’s security team via an audio and visual alert displayed on their control centre screen. Enabling them to quickly respond to incidents in the station, without having to constantly monitor camera footage.
In Las Vegas, city officials are using video data and other sensors to monitor activity and operations across the city. The system helps law enforcement and other emergency services to respond more readily to accidents and potential safety hazards. It also helps the city better manage its strapped resources because officials can see what’s happening at-a-glance.
Seeing through new lenses
In the future, this could expand beyond on-site cameras to include ones worn on the body or footage from smartphones. Many police forces now require officers to wear body cameras when out on patrol. Dashcams are becoming more commonplace - and every bystander has a smartphone. Linking these video sources into a central system could help uncover crime faster and provide valuable evidence.
Indeed, police forces will greatly benefit from mainstream adoption of the IoT because they’ll have visuals that they never had previously. Cameras owned by public bodies (like train stations) and those owned by private entities and individuals, can be used for facial recognition, crime identification and license plate tracking. A police station could see a live feed of a store burglary in action before officers even arrive at the shop.
Further data sources
IoT sensors embedded in public transport, street lighting and even roads and pavements could provide contextual data. Social media scanning combined with video data will provide early warnings of possible hate crime, gang violence or hooliganism. Several UK police forces are currently experimenting with live video and facial recognition technology to more effectively manage festivals, football matches, concerts and parades. Similar machine learning algorithms are being used to flag possible child abuse online.
City leaders will also gain a more comprehensive picture of the violence in their cities. Currently, violence is measured through crime statistics. However, this doesn’t give a complete view of the levels of violence in a population as some incidents aren’t reported and others don’t lead to prosecution. Violence costs the world 12.6% of its GDP every day. So calculating the level of violence on a city-by-city basis will give a baseline for fighting crime whilst also improving the bottom-line.
Laying the foundations
However, like anything worthwhile, building a safe city requires a lot of groundwork. Particularly with data management, governance and safety. Public and private bodies must be united under a common infrastructure, able to access a shared data management system that still remains secure-by-design. The type of data collected will be extremely sensitive in some cases and will require stringent protections. It will also have to comply with GDPR and any other local data regulations.
It will be overwhelming for a human team to monitor multiple simultaneous video feeds and data streams. Combining it within a VMS will be critical and automation will be required to sift through the noise. The data collected in a safe city will be vast and beyond human abilities to fully comprehend.
A call to action
Tomorrow’s safe cities are being built today. Although some of the technology, like AI, is still relatively new, that shouldn’t prevent city officials and law enforcement from experimenting with tools now.
Running pilot projects will provide lessons for the future, as well as improve digital literacy and stakeholder buy-in. Plus, many organisations are already benefitting from aspects of the safe city, like VMS technology. Rome wasn’t built in a day and neither will our future safe cities. So start as soon as possible.