Spatial Programming

What is Spatial Programming? Spatial programming refers to the art of creating complex (but simple to understand) programs which can control the movement and behavior of physical objects. This technology is used for everything from creating complex simulations of cities and environments to controlling digital military hardware such as robots and UAVs. Here are some of the main uses of spatial programming in the field of computer science and engineering:

Architectural Design

It is possible to design and program highly complex robots and other embedded systems using spatial programming. The modeling language used in this particular technology is called OpenSPL and is one of the many softwares we use when completing our architectural service base. This language is an open source project based upon the core technology of a novel open-source visualization library called Spatial Desktop.

Robotic Design and Planning

Strategic planning and manufacturing action can be improved through the application of high-level spatially distributed programming to manufacturing CAD systems. Large quantities of data can be processed rapidly through the use of sophisticated spatial programming techniques. Many robotic manufacturing applications and UAV designs utilize spatially distributed systems in the structural design and development of their components. In addition, some highly advanced robotic applications and UAV components are being developed which are capable of running on completely spatially distributed systems.

Environmental Planning and Design

Real-time environmental planning and design using high-level spatially distributed programs is now possible with the development of real-time 3D mapping and analysis space planning. This technology allows the tracking of resources and the analysis of large amounts of data to support efficient decision making and alterations. For example, real-time data obtained from an area of interest in a wild fire outbreak may be analyzed to determine how best to strategically avoid the spreading of the fire and control it. This will allow forest managers to make decisions that will reduce the risk of loss of life and property. Spatial programmed environmental planning and design (SPAD) techniques may also be applied to evaluate flood risk along coastal areas or evaluate urban growth and population health using large-scale maps.

Manufacturing Processes

The development of spatially distributed programming solutions has made it possible for production processes to be optimized around resources that maximize productivity. Optimized processes require the integration of the most appropriate information with the lowest amount of wasted resources. The development of embedded systems has made this possible. Embedded systems such as fault-tolerance engines and turbines have been developed to operate efficiently under high workloads without requiring manual assistance.

Geo-spatial Data visualization using R and Python libraries

The visualization of geographic data has become widely used both in the private and public sector due to its capability to give users a fast way to visualize large-scale data sets. Geo-spatial data visualization with Python and R is now available as open source software. Geo-spatial analysis and visualization using open source software offers the ability to access extremely high resolution satellite images, aerograms, and remote sensing data with a user-friendly interface.

Geo-spatial Software Development and Imaging

Geo-spatial software developers have produced software packages which include python bindings for a variety of remote sensing and surveying technologies. These software packages allow for the creation of interactive 3D models from satellite and airborne imagery, digital elevation data, or passive microwave images. These models can be used for concept design/development data, operational studies, schematic drawings, construction planning, environmental monitoring, disaster preparedness and response, archeological digs, and urban planning and design. Such software is designed to meet the needs of a wide variety of users by integrating well with other technologies and operating on a variety of operating platforms.

Spatial computing involves the use of a wide range of hardware and software to leverage the benefits of natural, man-made, or complex systems for solving a wide range of problems. The primary goal of spatial programming and software is to extend the capacity of human thought by modeling complex real-world phenomena. The spatial programming techniques used in the scientific community to solve problems also rely heavily on domain knowledge, e.g., Physicists attempt to solve problems concerning planetary satellites, lunar colonies, exoatmospheres, solar flares, etc. The technique is also used to solve crimes such as bank robbery, hijacking, or airplane collisions, which are on-going challenges in law enforcement agencies and the military. In general, the application of spatial computing techniques is being utilized to advance scientific research and make scientific observations.