SENSOR: signal events, neighbourhood security, order and reassurance.
What is SENSOR?
SENSOR is an intelligence orientated interview methodology designed to capture the public’s knowledge of neighbourhood crime and disorder and perceptions of risk. SENSOR is a tablet based data capture application that allows police and their partner agencies to identify and target the issues that have a disproportionate impact upon neighbourhood security. It thereby provides a mechanism for improving the effectiveness of interventions responding to community concerns. The SENSOR methodology was initially developed after intensive academic fieldwork conducted as part of the National Reassurance Policing Programme, and has been improved and refined by over 10 years deployment by councils and police forces.
What makes SENSOR different?
Three key innovations distinguish SENSOR from other surveys:
- In identifying signal crimes, signal disorders and control signals, it systematically focuses police resources upon those events that shape collective perceptions of risk. Significantly, the academic research demonstrates that this includes antisocial behaviour and incivility alongside more major crimes.
- Traditional survey methods have focused upon obtaining a random survey of public attitudes. The methodology underpinning SENSOR uses a purposive sample of ‘neighbourhood sentinels’, individuals with high knowledge of local neighbourhoods. This makes it both more effective and efficient to operate.
- Because it is an intelligence tool, it is operated by police staff, rather than outsourcing the data capture work to a market research agency. As a result, the process also meets demands for increased police-community engagement.
As a community intelligence methodology, SENSOR provides a diagnostic of how in ‘high information environments’ people attend to some information whilst cognitively ‘screening out’ other data in the formation of perceptions, opinions and attitudes.
In the policing sector SENSOR is coherent with and directly relevant to a number of current initiatives and programmes. Most notably:
- Neighbourhood Policing;
- Government focus on antisocial behaviour;
- Developing neighbourhood management agenda.
What are the benefits of SENSOR?
On the basis of the clients who have used SENSOR to date, a number of benefits of the process can be identified:
- Identifies the signal crimes and disorders that really matter to local communities thereby giving Neighbourhood Policing interventions enhanced impact;
- Identifies areas where local partner services should be targeted (e.g. council environmental services; traffic enforcement; fire prevention etc.);
- Establishes a community intelligence feed for force intelligence systems;
- Builds trust and confidence amongst key members of the public;
- Tests the integrity and robustness of Neighbourhood Policing processes from a citizen perspective;
- Introduces a new data stream of evaluative data on how local publics are judging the quality of police and partner services;
- Improves community engagement skills of front-line officers.
Development to date
Following intensive academic research on the Signal Crimes Perspective, a paper version of the tool was tested and validated by 3 police forces, with superior results to other methods. A laptop-based version of the data collection package (known as i-NSI) was tested and validated and has now been used successfully by over twenty force/local authority partnerships around the country and internationally within the last 10 years. The software has now been completely rewritten for a touch based interface, for much quicker, more intuitive, and portable application, while also allowing real-time data download.
In most projects to date, clients have preferred to work with staff from UPSI to manage the data capture and analysis process. However, training programmes to train client analysts and a ‘train-the-trainer package’ to enable in-house training of interviewers have also been successfully run.
Want to know more?
Read the full report on the UPSI website.
Download a pdf version of this briefing. (1007.13 kb)