Abstract: In various embodiments, a process for configuring or commissioning a solar power system includes receiving, at a controller, hardware identifiers of a plurality of power electronics modules to be configured. Each of the plurality of power electronics modules of at least a portion of the plurality of power electronics modules is associated with a corresponding photovoltaic panel. A hub is configured to wirelessly communicate with the plurality of power electronics modules. The controller is physically connected to the hub and communicates with the hub via wiring that also carries power from photovoltaic panels to an inverter. The process includes configuring, by the controller, the plurality of power electronics modules using the received hardware identifiers.

Abstract: In various embodiments, a process for configuring or commissioning a solar power system includes receiving, at a controller, hardware identifiers of a plurality of power electronics modules to be configured. Each of the plurality of power electronics modules of at least a portion of the plurality of power electronics modules is associated with a corresponding photovoltaic panel. A hub is configured to wirelessly communicate with the plurality of power electronics modules. The controller is physically connected to the hub and communicates with the hub via wiring that also carries power from photovoltaic panels to an inverter. The process includes configuring, by the controller, the plurality of power electronics modules using the received hardware identifiers.

Abstract: A portable disinfecting apparatus with effective disinfection properties against pathogens, such as bacteria, fungi, and viruses is disclosed. Embodiments of the portable disinfecting apparatus include a portable sterilization box having at least one path configured to receive drawn air and to irradiate the drawn air with UV radiation along the path to produce disinfected air. The path may be provided using baffles that are configured, for example, in a serpentine or spiral configuration to provide a non-linear flow path for the air. The UV light sources, such as UV LEDs may be mounted on the baffles. Embodiments of the apparatus include an intake tube connected to the sterilization box for drawing air into the sterilization box from a point high within the room that is to be disinfected. The disinfected air is released from the sterilization box a point lower in the room.

Abstract: A portable disinfecting apparatus with effective disinfection properties against pathogens, such as bacteria, fungi, and viruses is disclosed. Embodiments of the portable disinfecting apparatus include a portable sterilization box having at least one path configured to receive drawn air and to irradiate the drawn air with UV radiation along the path to produce disinfected air. The path may be provided using baffles that are configured, for example, in a serpentine or spiral configuration to provide a non-linear flow path for the air. The UV light sources, such as UV LEDs may be mounted on the baffles. Embodiments of the apparatus include an intake tube connected to the sterilization box for drawing air into the sterilization box from a point high within the room that is to be disinfected. The disinfected air is released from the sterilization box a point lower in the room.

Abstract: A 3D rendered image of a radar-scanned terrain surface is provided from a radar return signal from the surface, wherein the return signal includes data indicative of azimuth, elevation, and range of a radar-illuminated area of the surface. The data are processed for transformation into X, Y, and Z coordinates. The X and Y coordinates corresponding to each illuminated area are triangulated so as to create a mesh of triangles representing the terrain surface, each of the triangles in the mesh being defined by a vertex triplet. 3D imaging information (grey scale shading and/or coloring information) is added to each triangle in the mesh, based on the amplitude of the radar return signal from the coordinates represented by each vertex in the triplet and the value of the Z coordinate at each vertex, so as to form the 3D rendered image.

Abstract: The beach cart has two arcuate rails having two ends. Upon one end, the rails have a handle and on the other end, an axle and a pivoting plate. The axle spans the rails and has two wheels. The plate attaches to each rail at a hinge. The plate pivots from a position perpendicular to the rails to a position folded upon the rails. When unfolded, the plate supports cargo, and when folded, the plate supports a tabletop as the handle is positioned down and the cart positioned flat. Between the rails, a curved panel stiffens the cart. The curved panel has a tube in communication with two openings for carrying an umbrella. Centered at the crest of the panel, an aperture receives a beach umbrella when the invention is placed down at the beach.

Abstract: The beach cart has two arcuate rails having two ends. Upon one end, the rails have a handle and on the other end, an axle and a pivoting plate. The axle spans the rails and has two wheels. The plate attaches to each rail at a hinge. The plate pivots from a position perpendicular to the rails to a position folded upon the rails. When unfolded, the plate supports cargo, and when folded, the plate supports a tabletop as the handle is positioned down and the cart positioned flat. Between the rails, a curved panel stiffens the cart. The curved panel has a tube in communication with two openings for carrying an umbrella. Centered at the crest of the panel, an aperture receives a beach umbrella when the invention is placed down at the beach.

Abstract: A 3D rendered image of a radar-scanned terrain surface is provided from a radar return signal from the surface, wherein the return signal includes data indicative of azimuth, elevation, and range of a radar-illuminated area of the surface. The data are processed for transformation into X, Y, and Z coordinates. The X and Y coordinates corresponding to each illuminated area are triangulated so as to create a mesh of triangles representing the terrain surface, each of the triangles in the mesh being defined by a vertex triplet. 3D imaging information (grey scale shading and/or coloring information) is added to each triangle in the mesh, based on the amplitude of the radar return signal from the coordinates represented by each vertex in the triplet and the value of the Z coordinate at each vertex, so as to form the 3D rendered image.

Abstract: A 3D rendered image of a radar-scanned terrain surface is provided from a radar return signal from the surface, wherein the return signal includes data indicative of azimuth, elevation, and range of a radar-illuminated area of the surface. The data are processed for transformation into X, Y, and Z coordinates. The X and Y coordinates corresponding to each illuminated area are triangulated so as to create a mesh of triangles representing the terrain surface, each of the triangles in the mesh being defined by a vertex triplet. 3D imaging information (grey scale shading and/or coloring information) is added to each triangle in the mesh, based on the amplitude of the radar return signal from the coordinates represented by each vertex in the triplet and the value of the Z coordinate at each vertex, so as to form the 3D rendered image.

Abstract: A 3D rendered image of a radar-scanned terrain surface is provided from a radar return signal from the surface, wherein the return signal includes data indicative of azimuth, elevation, and range of a radar-illuminated area of the surface. The data are processed for transformation into X, Y, and Z coordinates. The X and Y coordinates corresponding to each illuminated area are triangulated so as to create a mesh of triangles representing the terrain surface, each of the triangles in the mesh being defined by a vertex triplet. 3D imaging information (grey scale shading and/or coloring information) is added to each triangle in the mesh, based on the amplitude of the radar return signal from the coordinates represented by each vertex in the triplet and the value of the Z coordinate at each vertex, so as to form the 3D rendered image.

Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads and/or from one or more other sources (such as physical sensors near to or embedded in the roads). The road traffic conditions assessment based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics of interest from the data samples. In some situations, the inferences include repeatedly determining current traffic flow characteristics and/or predicted future traffic flow characteristics for road segments of interest during time periods of interest, such as to determine average traffic speed, traffic volume and/or occupancy, and include weighting various data samples in various ways (e.g., based on a latency of the data samples and/or a source of the data samples).

Abstract: Techniques are described for automatically analyzing historical information about road traffic flow in order to generate representative information regarding current or future road traffic flow, and for using such generated representative traffic flow information. Representative traffic flow information may be generated for a variety of types of useful measures of traffic flow, such as for average speed at each of multiple road locations during each of multiple time periods. Generated representative traffic flow information may be used in various ways to assist in travel and for other purposes, such as to determine likely travel times and plan optimal routes. The historical traffic data used to generate the representative traffic flow information may include data readings from physical sensors that are near or embedded in the roads, and/or data samples from vehicles and other mobile data sources traveling on the roads.

Abstract: Techniques are described for displaying or otherwise providing information to users regarding various types of road traffic condition information in various ways. The information may be provided, for example, as part of a user interface (or “UI”), which may in some situations further include one or more types of user-selectable controls to allow a user to manipulate in various ways what road traffic condition information is displayed and/or how the information is displayed. A variety of types of road traffic condition information may be presented to users in various manners, including by presenting information on graphically displayed maps for geographic areas to indicate various information about road conditions in the geographic area. In addition, provided controls may allow users to select particular times, select particular routes, indicate to perform animation of various types of changing traffic conditions over a sequence of multiple successive times, etc.

Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads, as well as in some situations data from one or more other sources (such as physical sensors near to or embedded in the roads). The assessment of road traffic conditions based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics from the data samples. In some situations, the inferences based on the data samples includes repeatedly determining average speeds for road segments of interest during periods of time in such a manner as to weight various data samples for those road segments in various ways (e.g., based on a latency of the data samples and/or a source of the data samples).

Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads, as well as in some situations data from one or more other sources (such as physical sensors near to or embedded in the roads). The assessment of road traffic conditions based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics of interest from the data samples. In some situations, the filtering of the data samples includes identifying data samples that are inaccurate or otherwise unrepresentative of actual traffic condition characteristics of interest, such as by identifying data samples that are statistical outliers with respect to other data samples.

Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads, as well as in some situations data from one or more other sources (such as physical sensors near to or embedded in the roads). The assessment of road traffic conditions based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics from the data samples. In some situations, the inferences based on the data samples includes repeatedly determining traffic flow characteristics for road segments of interest during periods of time, such as to determine traffic volume and/or average occupancy of the road.

Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads, as well as in some situations data from one or more other sources (such as physical sensors near to or embedded in the roads). The assessment of road traffic conditions based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics of interest from the data samples. In some situations, at least some of the mobile data sources are configured to frequently acquire and store data samples, and to occasionally make multiple such data samples available together for use in the road traffic condition assessment (e.g., by acquiring a data sample every minute and by transmitting a group of stored data samples every 15 minutes).

Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads, as well as in some situations data from one or more other sources (such as physical sensors near to or embedded in the roads). The assessment of road traffic conditions based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics from the data samples. In some situations, the filtering of the data samples includes identifying data samples that are inaccurate or otherwise unrepresentative of actual traffic condition characteristics, such as data samples that are not of interest based at least in part on roads with which the data samples are associated and/or that otherwise reflect vehicle locations or activities that are not of interest.

Abstract: Techniques are described for generating predictions of future traffic conditions at multiple future times, such as by using probabilistic techniques to assess various input data while repeatedly producing future time series predictions for each of numerous road segments (e.g., in a real-time manner based on changing current conditions for a network of roads in a given geographic area). In some situations, one or more predictive Bayesian models and corresponding decision trees are automatically created for use in generating the future traffic condition predictions for each geographic area of interest, such as based on observed historical traffic conditions for those geographic areas. Predicted future traffic condition information may then be used in a variety of ways to assist in travel and for other purposes, such as to plan optimal routes through a network of roads based on predictions about traffic conditions for the roads at multiple future times.

Abstract: Computer system reliability is improved using various techniques to monitor objects (e.g., processes, threads, DLLs, etc.) executing on the system. Such techniques include active techniques, in which information is continually communicated from the object to the monitor, and passive techniques, in which the object does not need to repeatedly provide information to the monitor. The monitor determines when an object in the computer system has failed, and initiates appropriate recovery action when such a failure is detected.