Structured Information Management: Processing and Retrieval We work with developing new techniques for the management of data stored in very large information banks Main task is indexing documents and classifying their subjects, before intelligent storing data in an electronic information base from which they can then be retrieved using simple natural language search requests. Topics include information storage and retrieval, file inversion techniques, modelling the user, automatic indexing, language analysis, subject classification, and machine learning. The first mover on this issue was actually the ESPRIT II Project named SIMPR, which stands for Structured Information Management: Processing and Retrieval However, since back then many new, improved and emerging technologies have changed both what we focus on and the way we work. Technologies, communications, social media, data storage and analytics to proactively solve problems are used to maximize effectiveness and efficiency, and provide higher-quality services. But these technological advancements also create a new set of challenges – particularly around data’s explosive growth. According to many sources, the size of the digital universe will double every two years. These analytics are optionally validated by the user and then stored in indexes for subsequent search against keywords specified in a request for information. The prototype incorporates advanced linguistic software, performing morphological and syntactic analysis and disambiguation of texts. Advanced analytics help us meet these challenges - no matter what it is; technologies, telecommunications, social media, and cloud-based data storage. Consider the need to analyze ever-growing amounts of data streaming from sensors in devices such as streetlights, water meters, public transportation systems and more. Smart cities can overcome these challenges by establishing a strong analytical backbone – including a centralized data store – as the framework for city government - enabling them to deliver innovative services, support higher service levels and do more with less. For smart city initiatives to be successful and deliver expected benefits, elected leaders and their staffs need a clear and agreed-upon vision for the initiative and an approach that fits their capabilities and needs. Cities are contributing to this trend, generating vast amounts of new data in departments as varied as planning, utilities, public safety, education and finance. As data continues to grow, it becomes increasingly important for cities to quickly integrate and manage it all This study takes off with the findings and what has been achieved over the years - in order to take the full benefit from the advances in information management Our study; Based on Service Oriented Architecture we make identification of the various central / distributed platforms, data storage and search algorithms; Covering disciplines of Queuing Theory, Related Processes and Load Balancing, Queuing Delay, Control and Filtering Algorithms, Renewal Theory & Praxis, Relay and Processing, Document Handling, Tagging, Treading, Automatic Indexing and Subject Classification The SIMPR Team