Field of the Invention The present invention is directed to a method for cost-effective and efficient bandwidth adaptive transferring/recording sensory data from single or multiple data sources to network accessible storage devices. More particularly, the invention is a fault tolerant and efficient method for recording sensory data including video as received from a single or multiple number of data sources like Cameras to network accessible storage devices, estimation of optimal required bandwidth for individual data channels taking into consideration the data download speed from data source to server along with the availability of network bandwidth at any given point of time, efficient network bandwidth sharing amongst the data channels for uploading data to storage devices over network. Background of the Invention Video Management Systems are used for video data acquisition and search processes using single or multiple servers. They are often loosely coupled with one or more separate systems for performing operations on the acquired video data such as analyzing the video content, etc. Servers can record different types of data in storage media, and the storage media can be directly attached to the servers or accessed over IP network. This demands a significant amount of network bandwidth to receive data from the sensors (e.g, Cameras) and to concurrently transfer or upload the data in the storage media. Due to high demand in bandwidth to perform such tasks, especially for video data, often separate high speed network are dedicated to transfer data to storage media. Dedicated high speed network is costly and often require costly storage devices as well. Often this is overkill for low or moderately priced installations. It is also known that to back up against server failures, one or more dedicated fail- over (sometimes called mirror) servers are often deployed in prior art. Dedicated fail- over servers remain unused during normal operations and hence resulting in wastage of such costly resources. Also, a central server process either installed in the failover server or in a central server is required to initiate the back-up service, in case a server stops operating. This strategy does not avoid a single point of failure. Moreover, when the servers and clients reside over different ends in an internet and the connectivity suffers from low or widely varying bandwidth, transmission of multi- channel data from one point to another becomes a challenge. Data aggregation techniques are often applied in such cases which are computationally intensive or suffer from inter-channel interference, particularly for video, audio or other types of multimedia data. As regards analytic servers presently in use it is well known that there are many video analytics system in the prior art. Video content analysis is often done per frame basis which is mostly pre defined which make such systems lacking in desired efficiency of analytics but are also unnecessarily cost extensive with unwanted loss of valuable computing resources. Added to the above, in case of presently available techniques of video analysis ,cases of unacceptable number of false alarms are reported when the content analysis systems are deployed in a noisy environment for generating alerts in real time. This is because the traditional methods are not automatically adaptive to demography specific environmental conditions, varying illumination levels, varying behavioural and movement patterns of the moving objects in a scene, changes of appearance of colour in varying lighting conditions, changes of appearance of colours in global or regional illumination intensity and type of illumination, and similar other factors. It has therefore been a challenge to identify the appearance of a non-moving foreign object (static object) in a scene in presence of other moving objects, where the moving objects occasionally occlude the static object. Detection accuracy suffers in various degrees under different demographic conditions. Extraction of particular types of objects (e.g. face of a person, but not limited to) in images based on fiduciary points is a known technique. However, computational requirement is often too high for traditional classifier used for this purpose in the prior art, e.g., Haar classifier. Also, in a distributed system where multiple sites with independent administrative controls are present, unification of those systems through a central monitoring station may be required at any later point of time. This necessitates hardware and OS independence in addition to the backward compatibility of the underlying computational infrastructure components, and the software architecture should accommodate such amalgamation as well. It would be thus clearly apparent from the above state of the art that there is need for advancement in the art of sensory input/data such as video acquisition cum recording and /or analytics of such sensory inputs/data such as video feed adapted to facilitate fail-safe integration and /or optimized utilization of various sensory inputs for various utility applications including event/alert generation, recording and related aspects. Video Management System using IP enabled video capturing devices (Cameras etc) has become an integral part of Surveillance industry today. A basic requirement of this type of systems is to input compressed video streams from multiple cameras and record the video in storage devices. In the earlier days when DVR and then NVR were predominant components, the complexity and hence the challenges for efficient deployment of the system were less. This is because each DVR or NVR was a standalone system taking feed from a handful of cameras (typically 16 or 32), and used their dedicated local storage devices to record the video. However, when the number of cameras started to increase beyond 100, and typically to a few hundreds, and the users demanded a unified system to record, view and search video from these hundreds of cameras efficiently, Video Management System emerged as a solution. In a typical Video Management System there are multiple servers, each catering a set of Video Capture devices (e.g., Cameras), one or more network accessible RAID configured storage devices, and multiple workstations. Each server now needs to handle 64 or more cameras, stream the video from the cameras to the client machines. In a Video Management Server system, there is a requirement for an efficient Network bandwidth management, so that all the network bandwidth hungry tasks assigned to the servers, viz, grabbing video from IP- cameras, uploading video to Network accessible storage devices and streaming the video channels to the Clients on demand, are executed in an optimal way. Also, the system must be fault tolerant so that intermittent failure of the Network connectivity from the Server to the Network accessible storage devices does not result loss of video in the storage. All these activities should happen automatically without any user interaction. Due to high demand in bandwidth to perform such tasks, especially for video data, often separate high speed network are dedicated to transfer data to storage media. Dedicated high speed network is costly and often require costly storage devices as well. Often this is a overkill for low or moderately priced installations. However there has hardly been any choice because no effective strategy for network bandwidth sharing among multiple concurrent processes in a single server could be devised in traditional systems, particularly in a situation when the data sources stream data at variable bit rates, with prior art. The challenge here is to make the system efficient with respect to all the tasks mentioned above. Traditionally, systems are proposed where redundancy in terms of multiple network paths from storage devices to servers, very high speed storage network and redundant recording and streaming servers are used to cater to such problems. This incurs high cost and non-optimal use of the resources, as a sizable portion of the resource is underutilized or non-utilized under normal scenario. Objects of the Invention It is thus the basic object of the present invention to provide for a method for cost- effective and efficient transferring /recording sensory data from single or multiple data sources to network accessible storage devices. Another object is to propose a method for efficient transferring /recording sensory data which would be unique as it would handles all the above tasks in an efficient way, with optimal use of the resources (Network, Storage space), even using a decent server having only one Network interface card. A further object of the present invention is directed to advancements in method adapted for intelligently sharing the computing resource, storage, rendering devices and communication bandwidth among different processes of the system to execute the above mentioned tasks with limited resources. Another object of the present invention is directed to advancements in method discussed above by interconnecting a number of intelligent components consisting of hardware and software, and involving implementation techniques adapted to make the system efficient, scalable, cost effective, fail-safe, adaptive to various demographic conditions, adaptive to various computing and communication infrastructural facilities. Summary of the Invention Thus according to the basic aspect of the present invention there is provided According to another aspect of the invention there is provided a method for cost- effective and efficient transferring /recording sensory data from single or multiple data sources to network accessible storage devices comprising: atleast one sensory data recording server adapted to record inputs from single /multiple data sources in atleast one local storage space with the URL of the files stored in database; transferring the thus stored files from said local storage to a network based central storage provided for accessing the files for end use/applications, said transfer of sensory data from source to the central storage via said local storage being carried out taking into consideration the data download speed(inflow rate) from data source to server along with the availability of network bandwidth at any given point of time for efficient network bandwidth sharing amongst multiple data sources to said storage device in the network. In the above method wherein said sensory data recording server is adapted to monitor available total network bandwidth and per channel inflow rate and based thereon decide rate of per channel video transfer from the server local storage to said central storage. In the above method wherein sensory data from the source are recorded in the form of variable length clips wherein the clip duration is set by the user or set by the server itself. In the above method comprising the step of determining the optimal bit rate for uploading sensory inputs comprising the following steps: (a) calculating the average bit rate for each channel separately in periodic intervals wherein the sensory input streaming rate (DO of a particular source/camera (Q) camera to the server is estimated and (b) identifying the available network bandwidth (B) at that instant from the system; and finally (c ) calculating the frequency of Clip upload for channel, based on : where 0