Automated recognition of individuals and/or pre-determined traits or risk factors/criteria lies at the basis, indeed is the very raison d’être, of smart surveillance systems. Yet new EU regulations and specifically those on information sharing between police and security forces explicitly prohibit automated decision-taking regarding individuals unless “authorised by a law which also lays down measures to safeguard the data subject’s legitimate interests” (art 7, CFD 2008/977/JHA). Where are these laws, what can these measures be and what else should the laws contain? Can the laws be technology-neutral but sector specific, thus permitting a measured approach to the appropriateness of smart surveillance technologies? Can they be extended to all security applications of smart surveillance, even those not covered by CFD 2008/977/JHA? This project (SMART) addresses these and other questions through a comprehensive approach which combines a technical review of key application areas by sector with a review of existing pertinent legislation to then produce sets of guidelines and a model law compliant with CFD 2008/977/JHA and EU Directive 46/95. The project first focuses on one meaning of “measures” i.e. it uses expertise from police and security forces from inside and outside the EU to “measure” (as in “calculate”) risk factors in a number of priority application areas for smart surveillance technologies including border control, crowd-control, counter-terrorism and e-government. It also evaluates the appropriateness and available safeguards for on-line surveillance and associated risks inherent in data-sharing and exchange. Having thus identified appropriate instances of application as well as a number of options for safeguards, the project moves on to create a tool-kit useful to system designers and policy makers across Europe comprising system design/operational guidelines and a model law which would contain a number of scalable measures providing adequate safeguards.