1: Distributed Intelligent Systems and Natural Collective Intelligent Systems 1.1. Introduction: Background and Driving Forces 1.2. DIS short classification 1.3. Natural collective intelligent systems 1.4. Ant colony 1.5. Bee colony 1.6. Collective movements in nature 2: Multisensor Systems 2.1. Interaction of the system with the external environment 2.2. Sensor classification 2.3. Multisensory systems 2.4. Conclusion 3: Smart Cities Based on Multisensor Systems 3.1. Introduction 3.2. The main characteristics of the smart city 3.3. Biometric sensors in a smart city 4: Biometric Characteristics 4.1. Static biometric characteristics 4.2. Dynamic biometric characteristics 4.3. Multimodality of biometric identification 5: Biometric Data Processing in Smart Cities Based on Multisensor Systems 5.1 Uniform City biometric community 5.2 Biometric features in the smart city 5.3 Human face image analysis 5.4 Analysis of the geometry of the auricle 5.5 Human gait analysis 6: General Information about Parallel Shift Technology 6.1. Theoretical Foundations of parallel shift technology 6.2. Data generation and storage 6.3. Vector formation of functions of the area of intersection 6.4. Formation of FAIs sets for non-binary images 6.5. Noise control with the use of PST 7: Image Recovery by Methods of Parallel Shift Technology 7.1. The method of circumscribed rectangles 7.2. Determining the parameters of circumscribed rectangles 7.3. Formation of reference surfaces for parts of the existing standard 8: Scene Analysis for Two Objects 8.1. Determining the basic parameters of the scene 8.2. Determining the real values of the basic parameters of the scene objects 8.3. Determining the shape of the objects of scene 8.4. The order for determining the basic parameters of the scene 9: Radon Transformation Technology on Cellular Automata with Hexagonal Coating 9.1. Introduction 9.2. Images description technology based on cellular automata with hexagonal coated Radon transform 10: Biometric Identification Methods Based on the Geometry of the Auricle based on Parallel Shift Technology and Radon Transformation 10.1. Technologies for biometric identification 10.2. Biometric identification methods based on the analysis of the auricle 10.3. Determination of the area of recognition in biometric identification by the shape of the ear based on the parallel shift technology 10.4. Determining the cut-off points of the ear image 10.5. The method of dividing the image into individual objects 10.6. The actual application of the method of determining the location of the image of the ear 10.7. The procedure for comparing the elements of the ear image with the reference data 11: Methods of Biometric Identification Based on Gait in the Smart City 11.1. The main reasons for using human gait for biometric identification in a smart city 11.2. Description of gait identification method 11.3. Search for the motion vector of the object in the visual field and the gaite period 11.4. Defining the area of analysis in the images of the silhouette of the object 11.5. Comparison of the obtained data with the reference information 12: Biometric Data Processing of Human and Animal Colonies in a Smart City 12.1. Distributed smart sensor network of smart city 12.2. A method for analyzing the overall urban picture of the behavior of people and animals in a smart city 12.3. Selection and description of objects in the visual scene 12.4. Time impulse description of the visual picture of a smart city 13: Behavioral Models of Human and Animal Colonies Based on the Technology of Cellular Automata with Active Cells 13.1. Theoretical positions cellular automata technology with active cells 13.2. Interaction of active cells 13.3. Colony formation 13.4. Cell colony movement 13.5. Interaction of active cell colonies References

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