There is provided a system for altering video which includes at least one camera sending video feed to a hardware module or a software module. The module maintains a predefined amount of pre-roll past video frames to a triggering motion event. The pre-roll past video frames are sent upon connection by a user to a real time video feed display in a fast forward manner and the video stream is switched to real time video after receipt of the pre-roll past video frames.

Methods and apparatus for identification and characterization of latency in a content delivery network. In one embodiment, interaction of users with content is recorded via collection of tuning records; the latency is then utilized to adjust the timing on the tuning records to account for lapses in time for sending these between entities of the network and the user devices, and for processing occurring at the devices. The latency is determined by taking into account a device specific latency component, and a network latency component. The network latency component is determined in one variant by sending a message to the device from the network requesting a response. Once the timing of the tuning records is adjusted, these tuning records may be relied upon as being accurate on a second-by-second basis. Accordingly, tuning records may be obtained and analyzed for content which lasts for a very short period of time.

An example method comprises: receiving, at a server from a first client device, a request for access to a client feature on the first client device; determining, by the server, an applicable rule for the access request, the applicable rule having a plurality of nodes; determining, by the server, device capabilities needed for the determined rule; determining, by the server, nodes that can be executed and nodes that cannot be executed, based on the device capabilities, the nodes that can be executed including device hardware capabilities and the nodes that cannot be executed including real-time device capabilities; executing, by the server nodes that can be executed to reach a partial decision for the applicable rule; pruning the applicable rule to remove executed nodes and generate a pruned rule that includes nodes that cannot be executed; transmitting the pruned rule and partial decision to the first client device.

Systems and methods are provided for selecting one or more network-connected devices to provide device functions required by an event. A media guidance application may detect an event in which a user is currently engaged. The media guidance application may identify a set of device capabilities associated with the event. The media guidance application may search, within a plurality of network-connected devices of the user, to identify one or more devices that enable functions corresponding to the set of device capabilities to be perceptible to the user, and the media guidance application may instruct the identified one or more devices to provide the functions corresponding to the set of device capabilities associated with the event.

Methods, systems, and computer readable media may be operable to facilitate the dynamic selection of a storage device for storing media. When a recording request is received, storage information associated with resources of one or more networks and one or more storage devices may be retrieved, and a network may be selected for recording and storing the requested media based upon an algorithm that considers the retrieved information. One or more specific storage devices located on the selected network may be selected for recording and storing the requested media. The selection of the one or more specific storage devices may be made based upon an algorithm that considers the available resources and capabilities of available storage devices.

Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying in return path data a first group of set top boxes classified as likely to exhibit machine events in tuning data of the return path data more frequently than a second group of set top boxes represented in the return path data. Additionally, in some examples, the method includes determining whether the first group of set top boxes includes a machine event based on a pattern of the tuning data in the return path data for respective ones of the first group of set top boxes and improving an accuracy of return path data by rectifying the machine event.

Systems and methods are described herein for streaming during unavailability of a content server. Upon determining that there are conditions indicating buffering issues during delivery of a media asset, a server determines a first group of devices suitable for receiving the media asset from the server and sharing the media asset on a peer-to-peer network. Then, the server determines a second group of devices suitable for receiving the media asset on a peer-to-peer network from a first group device. The server then determines groupings within which to share and receive the media asset. Next, the server transmits instructions to the devices in the first group to maintain in buffer and share certain portions of the media asset with the second group devices within their grouping. Finally, the server updates information detailing the media asset portions the devices are maintaining in buffer and sharing.

System and methods for cold-starting content on a platform using machine learning including: identifying content metadata and contextual data both corresponding to a target content item; generating a target content item model by applying deep neural learning that: applies a word vector embedding operation to the content metadata to generate a collaborative filtering representation of the content metadata, applies a word vector embedding operation to the contextual data to generate a collaborative filtering representation of the contextual data, and bridges the collaborative filtering representations of the content metadata and the contextual data to generate the target content item model; applying deep neural learning to compare the target content item model with a set of existing content item models; determining cold-start characteristics of the target content item based on the comparison; and providing the cold-start characteristics for distribution management of the target content item.

Disclosed are a method of transmitting image data having a hybrid resolution and a method of generating a hybrid-resolution image. A main region of an original image is transmitted as a high-resolution image and the remaining regions are transmitted as a low-resolution background image. Accordingly, an amount of data to be transmitted is able to be reduced.

Aspects of the subject disclosure may include, for example, a method comprising receiving one or more media content items; creating one or more leveraged content items from the media content item(s) by extracting one or more leverage points from the media content item(s); obtaining user information, such as user preferences and user context; selecting a selected content item from the leveraged content item(s) based on the user information; creating a custom content item by further extracting a subset of the leverage points from the selected content item based on the user information; and presenting the custom content item to the user's equipment. Other embodiments are disclosed.