On a normal day there is about 262 megabytes of data traffic per square kilometer. On a festival day that rises to 33,000 megabytes per square kilometer.
Our public life de facto largely takes place in the public spaces.
Open spaces are usually in the open air; however, these can also be part of municipal institutions and other (semi-) government buildings. Public spaces are not only limited to physical places, but also relate to the “mental and social” spaces. This implies that public spaces should allow citizens to be themselves without unsolicited interference from others. An important feature of the public spaces is that they are usually multi-functional, and as such are used for summer / winter events, including music festivals, public holidays, markets, and so on.
Every year an abundance of large and small events (>1000) take place in such public spaces in the Netherlands. It is not uncommon for unsafe situations to occur at these events, sometimes resulting in serious incidents.
Safety plays a crucial role in public spaces given the massive influx of people. Many issues can arise like noise, crime, riots, harassment, pollution, environmental crimes, fires, undesirable social behavior, looting, public drunkenness, dehydration, drug incidents, bacterial infections, and a multitude of other dangers that affect the quality of life.
Public order and safety in public areas is generally guaranteed by an integrated approach of organizers,
municipalities, law enforcement officers (including private security services), fire brigades and emergency
medical services, including first aid. A wide range of instruments is used by these chain partners, including
drawing up scenarios, crowd management, risk analyzes for foreseen and unforeseen threats, event permits, briefing, and investigation.
Although such approaches do have a positive impact on supervision and enforcement in public areas, it can be concluded at the same time that much can still be improved.
The smarter collection and use of data, interpretation from the operation, as well as the more sophisticated
collaboration based on data and interpretation, seems potentially a decisive weapon in the fight against disorder
and insecurity in public spaces.
Phase 1: Prepare & Test
During this phase the algorithms for the data safety experiments are trained exploiting a variety of machine learning techniques.
Phase 2: Operate and Monitor
This involves the actual setup and operation of the experiments in a controlled environment. During the experiments the training algorithms (e.g., for moshpit identification and prediction) are further explored and improved.
Phase 3: Learning & Sharing
The final stage pertains to learning from the experiments. Not only technical elements are considered, but also socio-organizational issues.