House of Quality for Safe Cities

Introduction

The safe city concept is practically new and is handled as a result of Crime Prevention Through Environmental Design (CPTED). Safe City is an idea in a community that uses technology to help governments, communities and businesses reduce the possibility of crime and provide an environment where people feel safe and comfortable (Smith, 2020). We also consider the safe city as the influence of diverse technologies (combinatorial Optimization, Machine Learning, Big Data, data visualisation, Internet of Things, Big-Data Analytics, software and others) to enhance the service quality of security objects. Secure city in a Smart City has three general kinds of problems and ways to resolve them:

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  Security-Hard problems. The Security-hard problems can be optimised (from Combinatorial Optimization: maximisation or minimisation) of the public security's resources.

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  Security-Soft problems. The security-soft problems are a fuzzy concept used to drive specific security government agendas and others. The security-Soft Problems are the security problems that handle information inaccurate or incomplete, with uncertainty and ambiguity, volatile, poorly understood and dynamics (security public policy, administration, decision-making, security government reforms).

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  Security-wicked problems. The complex, intractable, open-ended and wicked security problems are a problem that is difficult or impossible to solve because it presents incomplete, contradictory and changing requirements that are generally difficult to recognise. This problem requires deliberation and debate.

The components of a safe city are (Figure 1). In this document, we propose the idea components as parts of a jigsaw puzzle, where each piece of the puzzle is an important and unique element that interacts to form the secure city comprehensively. This puzzle can be updated and improved as time and generations change, to obtain better secure cities: