Recently, I was exposed to Spatial Computing. However, I didn't fully understand what it meant. I did some research. The first thing I looked for was what the term meant, the second one was, use-cases. The reason use-cases are important is that we need to be practical and think where we meet spatial computing in our day to day lives. How we can use it. Can we make it better? smarter? perhaps even more efficient.
First step: What does it mean?
Spatial - "Of or relating to space". But what is "space"?
Space - this is the boundless three-dimensional extent in which objects and events have relative position and direction. Physical space is often conceived in three linear dimensions, although modern physicists usually consider it to a boundless four-dimensional continuum known as spacetime. The fourth dimension is time.
Computing - Computing is any activity that uses computers to manage, process, and communicate information. It includes the development of both hardware and software.
Combining the two together means that we do some computation on events and/or objects that exist in our surroundings. The events come from things that happen in our physical space. An example is driving a car.
While driving a car there are multiple events that we compute and perform in real-time and space::
Cars use-case:
Our brain processes the image of the car, so we understand that physically this is a car. This is image processing. We often use some form of ignition to start the engine, some kind of keys, which can define as a form of security. For identity authentication, we refer to three types of identity prof:
what you know - password
what you have - physical keys
what you are - your unique fingerprint
We now begin driving. Our brain processes the images around us in order for us to drive safely, taking us from one point to the other, hopefully without casualties or accidents. This is where spatial computing kicks in; helping us to get from one place to the other safely while collecting information in the shape of events from the car itself - engine, brakes, speed, sensors. We also gather information from the space around us: other cars, children crossing the road, the physical environment or reality and so much more.
Where is the computing part of cars? When we combine the information collected from the car and its surroundings we can act on it. But first, we need to know how! This is where computation kicks in. Image recognition, ML-based algorithms or a set of rules help us to get a better picture of what is happening in the space around us.
Use-cases in Smart Cities:
A smart city is the use of data and technology to create efficiencies, improve sustainability, create economic development, and enhance the quality of life factors for people living and working in the city. An interesting startup in the field is ZenCity. ZenCity is helping governments to make a data-driven decision to improve residents' lives. This is manifested in a comprehensive understanding of the neighborhoods using AI at all levels, including on the ground changes in public transportation in order to reduce the use of cars. This is done with data, probably Big Data that was collected from
various sensors. Other examples of use-cases in smart cities
could be smart building, measuring energy consumption, and air quality,
temperatures and more.
MR/AR/VR Technology::
Mixed Reality(MR) is a combination of Augmented Reality (AR) and Virtual Reality(VR) resigning in combining the outdoors and physical reality with one generated by the use of a digital/computer engineering.
The most known tech is the MR glasses, similar to the famous Hololens. These glasses come with various sensors and an engine. For example, distinct sensors hardware that you can install almost everywhere. There are many real time use-cases for them such as, enriching the immediate knowledge we have in construction sites, and helping to create safer work environments. Another one includes remote support - sharing the view of what is happening in one place to bring support and help people in another area.
💡 Now that you know more about Spatial Computing, where do you use it in your daily life? What do you want to change and how?
Just a note
We didn't discuss Privacy , Data Processing at Scale and Machine Learning, but they have a LOT to do with Spatial computing as we collect data from surroundings and act on it in order to help improve peoples' lives. We should always have these in mind when we think of the kinds of uses-cases solutions from an engineering and creative perspective.
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