Development of the TIRAMISU Advanced Intelligence Decision Support System

ABSTRACT The Advanced Intelligence Decision Support System (AIDSS) is the first mine action technology in humanitarian demining to combine remote sensing and data fusion methods with advanced surveillance and reconnaissance in a successful operational system. It aims to provide a reliable, efficient tool to support the process of making decisions about suspected hazardous areas, based on the methodology scientifically developed and validated in the FP5 SMART project. The system was developed through Technology Project TP-006/0007-01, supported by the Ministry of Science, Education and Sports of the Republic of Croatia, and deployed in operations in several suspected hazardous areas in Croatia and Bosnia and Herzegovina in 2008 and 2016. It was upgraded in the TIRAMISU project, and its name changed to TIRAMISU Advanced Intelligence Decision Support System. Gaps identified by end-users and system operators were filled in. Among the main results were innovations for generating mine danger maps. In this paper, only the structure of the system and its potential application in non-technical surveys as part of humanitarian demining are shown.

[1]  Hichem Sahli,et al.  REMOTE SENSING MINEFIELD AREA REDUCTION: MODEL-BASED APPROACHES FOR THE EXTRACTION OF MINEFIELD INDICATORS , 2004 .

[2]  Thomas Justus Nolan,et al.  Geographic Information Science as a Method of Integrating History and Archaeology for Battlefield Interpretation , 2007 .

[3]  Maki K. Habib,et al.  Humanitarian Demining: Reality and the Challenge of Technology – The State of the Arts , 2007 .

[4]  Maki K. Habib,et al.  Humanitarian demining mine detection and sensors , 2011, 2011 IEEE International Symposium on Industrial Electronics.

[5]  Laurence Tianruo Yang,et al.  Fuzzy Logic with Engineering Applications , 1999 .

[6]  Andrija Krtalić,et al.  Analytical assessment for the process of collecting additional data on a suspected hazardous area in humanitarian demining , 2014 .

[7]  Milan Bajic.  The Advanced Intelligence Decision Support System for the Assessment of Mine-suspected Areas , 2010 .

[8]  Hansie Heymans,et al.  Effectiveness of GIS in Mine Action , 2015 .

[9]  Acheroy Marc,et al.  Mine-suspected Area Reduction Using Aerial and Satellite Images , 2008 .

[10]  Charles Mather,et al.  GEOGRAPHICAL INFORMATION SYSTEMS AND HUMANITARIAN DEMMING , 2000 .

[11]  Charles Conley,et al.  Landmines and Local Community Adaptation , 2002 .

[12]  Ivan Racetin,et al.  Methodology for semi‐automatic interpretation of digital multisensor images for the purpose of detection and extraction of unexploded ordnances , 2019 .

[13]  Y. Yvinec.  A validated method to help area reduction in mine action with remote sensing data , 2005, ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005..

[14]  Hrvoje Gold,et al.  Fusion of data, a priori information, contextual information and experts’ knowledge for decision making support in mine suspected area reduction , 2019 .

[15]  Snjezana Knezic,et al.  GIS‐based DSS for priority setting in humanitarian mine‐action , 2006, Int. J. Geogr. Inf. Sci..

[16]  Hichem Sahli,et al.  Comparison of spatial and aspatial logistic regression models for landmine risk mapping , 2016 .

[17]  Sabine Vanhuysse,et al.  Object‐Based image analysis for detecting indicators of mine presence to support suspected hazardous area re‐delineation , 2014 .

[18]  Isabelle Bloch,et al.  Space and airborne Mined Area Reduction Tools , 2003 .

[19]  Bob Eaton.  Area Reduction: A Solution Whose Time has Come , 2003 .

[20]  John M. Irvine.  National Imagery Interpretability Rating Scale (NIIRS) , 2015 .

[21]  Hichem Sahli,et al.  Hazard Mapping of Landmines and ERW Using Geo-Spatial Techniques , 2017 .

[22]  Hichem Sahli,et al.  Remote Sensing Minefield Area Reduction: Semantic Knowledge-Based Image Understanding , 2004 .

[23]  Marko Mladineo,et al.  Project management in mine actions using Multi-Criteria- Analysis-based decision support system , 2014 .

[24]  Anders Törne,et al.  A Semantic Approach to Information Management and Decision Support: An Application to Humanitarian Demining Operations , 2015, 2015 European Intelligence and Security Informatics Conference.

[25]  Love Ekenberg,et al.  Non-Technical Survey: A Model for Evidence-Based Assessment , 2010 .

[26]  Juraj Bartolic,et al.  10 years of work of Croatian scientists on the problems of demining , 2008 .

[27]  Hichem Sahli,et al.  Combined spatial point pattern analysis and remote sensing for assessing landmine affected areas , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[28]  P. M. Blagden.  The changing scene of mine clearance , 1998 .

[29]  Vinciane Lacroix,et al.  Indicators of Mine Presence: Focus on trenches , 2014 .

[30]  Yann Yvinec.  European Project of Remote Detection: SMART in a nutshell , 2004 .

[31]  Marc Acheroy,et al.  A GEOGRAPHICAL INFORMATION SYSTEM FOR HUMANITARIAN DEMINING , 2000 .

[32]  R. Weibel,et al.  Methods for visualizing the explosive remnants of war , 2013 .

[33]  A. Katartzis,et al.  Digital Signal/image Processing for Mine Detection. Part 1 : Airborne Approach , 1999 .

[34]  Ivan Racetin,et al.  TIRAMISU Methodology for Semi-Automated Interpretation of Digital Multisensor Images , 2018 .

[35]  Thomas L. Saaty,et al.  Models, Methods, Concepts & Applications of the Analytic Hierarchy Process , 2012 .

[36]  Hichem Sahli,et al.  Application of density analysis for landmine risk mapping , 2011, Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services.

[37]  Isabelle Bloch,et al.  Multisensor Data Fusion for Spaceborne and Airborne Reduction of Mine Suspected Areas , 2007 .

[38]  Sabine Vanhuysse,et al.  Final Report, Space and Airborne Mined Area Reduction Tools, project SMART, European Commission IST-2000-25044 , 2005 .

[39]  Dirk Borghys,et al.  Remote Sensing for Non‐Technical Survey , 2017 .