CONCEPTS AND ITS IMPLEMENTATION ON A SMART ENVIRONMENT INFANT RAJU RCollege Loyola-ICAM College of Engineering and Technology Email IDinfantraju

CONCEPTS AND ITS IMPLEMENTATION ON A SMART ENVIRONMENT INFANT RAJU RCollege Loyola-ICAM College of Engineering and Technology Email [email protected] InformationTechnolgy NAVEEN KUMAR V.GCollege Loyola-ICAM College of Engineering and Technology Email [email protected] InformationTechnolgy Abstract Ambient intelligence is one of the new discipline that makes thing around us to be intelligence and makes the environments more sensitive to us .This Ambient Intelligence largely depends upon the combinational technology which is deployed in sensors and devices which are more possibly connected to the network , as well as on the intelligence of the decision making used in the implementation part. The aims of this paper is to describe the characteristics and application of Ambient Intelligence, to provide examples of their applications and to quote the innovations that lies ahead in society for the implementation, In particular we mainly focus on the research and development that makes AMI technologies intelligent. Especially for the Software Engineering and information technologies expert communities. Keywords AMI- Ambient intelligence. Introduction The European Commissions on Information Society Technologies Advisory Group (ISTAG) introduced the concept of ambient intelligence. Basically, AMI refers to a digital and smart environment that actively, and sensibly, supports people in day to day activitiess. IEEE Intelligent Systems was one of the first technical publications to emphasize AMIs importance, with Nigel Shad bolts editorial in the July/August 2003 issue. Other concepts such as ubiquitous computing, pervasive computing, context awareness, and embedded systems that is overlapped with AMI, but there are distinctive differences between them. Networks, Sensors, Human Computer Interfaces (HCI), Pervasive Ubiquitous Computing and Artificial Intelligence (AI) these are all relevant and interdependent groups but none of them conceptually covers the full scope of AMI. Ambient Intelligence to put it in a nutshell all these resources are to provide a flexible and intelligent services to users acting in their environments that intern makes an smart environment. AMI is aligned with the concept of the disappearing computer . what is aml Conceptual Entity Ambient Intelligence has been characterized by research and developing people in many ways. These definition, are summarized and the features are highlighted where which AMI technologies are categorized in following manners such as sensitive, responsive, adaptive, transparent, ubiquitous, and intelligent computing. From these definitions, which are used in the process to characterize Ambient Intelligence, we can see how the other domains compares and contrasts these fields such as pervasive and ubiquitous computing, and artificial intelligence in their own manner. The fact that AMI systems must be sensitive, responsive, and adaptive is only due the highlights which depended on that of AMI researches on context-aware computing. Similarly, the AMI feature of transparency is certainly aligned with the concept of the disappearing computer. AMI researches are majorly involved in works on hearing, vision, language, and knowledge, which are all related to human intelligence, and there is where AMI differrs from ubiquitous computing. By drawing some advances concepts in artificial intelligence, AMI systems can be even more sensitive, responsive, adaptive, and ubiquitous. We characterize the development and the basis of this AMI technologies by the figure below (Fig1). The reviews and its implementation part of this technology in discussed the following section of the paper and also the advances that have been made in related areas that contribute to the goal of AMI systems that we have set forth. (Fig.1) INCLUDEPICTURE https//csdl-images.computer.org/mags/ex/2008/02/figures/mex20080200151.gif MERGEFORMATINET It is AMI works by bringing all the information that flexible to the machine and available contents, which provides us the intelligent service to users which is readily applied in the environment. Ambient Intelligence is one of the mechanisms that rule environment over its smartness ,The definition which is given above includes the need for a sensible system, and this means a system with intelligence. Contributing Technologies We categorize the contributing technologies of AMI into three areas (majorly). A key factor in AMI research is the presence of intelligence in things(objects) present in the environment. As such, the AMI too follows some algorithm to obtain data, and to perceives the state of the environment where the sensors, reasoning skills are of data collection is done by various AI techniques, and acts upon the environment by controllers to control their activities in such a way that the algorithm achieves its intended goal. Hence we focus on technologies that assist with sensing, reasoning, and acting(modeling). Sensing Because Ambient Intelligence specially made for real time application on the physical environments, an effective use of sensors is vital in the AMI . where which Without physical components that allow an intelligent agent to sense upon the environment and act accordingly, where in other end up with theoretical algorithms which have no practical use. Sensors are the key that links the available computational power in collaborating with the physical applications which are human-centric . Reasoning In order to make such algorithms responsive, adaptive, and more useful to the users, a reasoning activity should take as the part of the computing. These include in user modeling, activity prediction and also some part of the recognition, and a wide range of decision making ability, and spatial-temporal reasoning is also needed. Modeling modeling is One of the feature that separates general computing algorithms from the normal responsive algorithm .which create a possible way to detect the user ideology . If such a thing is possible then, it can be used to customize the behavior of the AMI software toward the users wish. Application for aml These Intelligence have their applications as follows Health-related applications By monitoring patients health and progress by performing automatic analysis of activities in their rooms hospitals can increase the efficiency of their services They can also increase their hospital safety by allowing authorized personnel and patients to gain access to specific areas and devices. Public transportation sector The traffic flow can be made more fluent, more efficient and safe by including extra technology known as Global Position Satellite (GPS)-based spatial location estimation. The tracking of vehicle citizens privacy issues and raising freedom of movement can also be facilitated by this approach Education services The smart card technology can be used to permit access to library facilities, car parkings,and lecture rooms in universities and higher educational institutes.The same smart card technology is also used for attendance monitoring, and tracking progression of students. Emergency services Security related administrations like rescue vehicle and fire units can enhance their response time to an occurrence by exact GPS based area and by speeding up the course via robotizing movement motions to support them. The prison and police administration can rapidly find a place where a risk is happening and get ready better access to it for security staff. Public Surveillance The broad arrangement of CCTV cameras gives checking of conceivably hazardous areas Downtown areas, underground stations and open transport would be able to profit for expanded surveillance . As of not long ago this was a totally detached process, regularly used to assemble confirmation of wrong-doing, yet restricted regarding crime avoidance. As video turns out to be consequently investigated and translated by PC this will stretch out AMI to the high extents. System Flow An AMI system can be built in many ways. Typically it needs sensors and devices to surround occupants of an environment (interactors) with technology (we can call this an e-bubble). The technology can provide accurate data to the system on the different contexts which are continuously developing. The data collected is transmitted by a network and pre-processed by middleware, which collates and harmonizes data from different devices. In order to make decision-making easier and more beneficial to the occupants of the environment the system will have a higher level layer of reasoning which will accomplish diagnosis and advise or assist humans with responsibility for intervention. (Fig.2) Elements that may be included in the high level Decision Making process are a Knowledge Repository where the events are collected and an AI Reasoner which will apply for example spatio-temporal reasoning to take decisions. For example, a decision could be to perform some action in the environment and this is enabled via Actuators. Knowledge discovery and machine learning techniques learn from the acquired information in order to update the AI Reasoner in the light of experience of the system. A typical information flow for AMI systems is depicted in Figure 2. AMI systems with the general architecture described in the previous section can be deployed in many possible environments. SMART Environment According to Pike Research on Smart Cities, the Smart city market is estimated at hundreds of billion dollars by 2020, with an annual spending reaching nearly 16 billion. This market springs from the synergic interconnection of key industry and service sectors, such as Smart Governance, Smart Mobility, Smart Utilities, Smart Buildings, and Smart Environment. These sectors have also been considered in the European Smart Cities project (http//www.smart-cities.eu) to define a ranking criterion that can be used to assess the level of smartness of European cities. Nowadays, machine learning is widely used, so AMI will likely also need to handle this technology. One requirement for AMI is to learn by observing users. Several systems understand user commands, but theyre not intelligent enough to avoid doing things that the user doesnt want. Basic machine learning methods will enable AMI systems to learn by observing users, thus making these systems more acceptable to them. As we mentioned before, automated devices such as robots could perform actions. Cognitive-robotics research can provide benefits for AMI environments such as smart homes. This is especially true when persons live alone, are elderly, or have health problems. The creation of intelligent robots that can perform several tasks or just act as companions is important. However, in the current state of the art, we can create robots that operate well only for specific tasks. Creating robots with the flexibility to do different tasks, as humans can do, is too complex. This limitation is due primarily to physical constraints. Pike research on Smart Cities Online.Available http//www.pikeresearch. com/research/smart-cities. Injectable Technologies Injectable technologies is an one part of the upcoming AMI by which, it enables us to possibly to create a virtual assistant of yourself, so that is can be readily implemented in the hardware and can be readily use in a wide range of things available. ACKNOWLEDGEMENT We wish to thank Mrs. G. Shobana of IT department and Mr.Emmanuel of ECE department for their encouragement and support of this Paper. We are also grateful for their assistance with the production of this paper.Many thanks go to the contributors of the chapter. Their active and timely cooperation is highly appreciated. References J.C. Augusto, and P. McCullagh, Ambient Intelligence Concepts and Applications, Intl J. Computer Science and Information Systems, vol. 4, no. 1, 2007, pp. 128. 5.N. Shadbolt, Ambient Intelligence, IEEE Intelligent Systems, vol. 18, no. 4, 2003, pp. 23. C. Ramos, Ambient Intelligencea State of the Art from Artificial Intelligence Perspective, Proc. 13th Portuguese Conf. Artificial Intelligence Workshops, LNAI 4874, Springer, 2007, pp. 285295. IST Advisory Group, Ambient Intelligence From Vision to Reality, European Commission, 2003 okia,2006. research.nokia.com/research/projects/sensorplanet/ ., Aarts E,de Ruyter B (2009) research perspectives on ambient intel. Journal on Ambient Intelligence and Smart Environments (JAISE) Aarts E,Harwig R, SchuurmansM(2002) Ambient intelligence. In The invisible future the seamless integration of technology into everyday life, McGraw-Hill, pp 235250 . AUTHORS PROFILE Mr INFANT RAJU R is currently pursuing his undergraduate studies in the field of INFORMATION TECHNOLOGY at LOYOLA-ICAM college of Engineering and Technology,Chennai. Mr NAVEEN KUMARV.G. is currently pursuing his undergraduate studies in the field of INFORMATION TECHNOLOGY at LOYOLA-ICAM College of Engineering and Technology,Chennai. Type text Lap.Q)f0WFV45OXZ qHSMoPDv zxfC64MDwq Bor M RO6NTEc) HkP,QOpDUtXVz 3 w-Oyh,MMNtXMDXpRR,[email protected]
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