iCrowd Newswire – Sep 17, 2020
The existing infrastructure is not able to cope up with speed and spread of the digital revolution. The automotive navigation, logistics, and deliveries are witnessing implications due to incorrect address point. Every country depends on the addressing system, despite the advancement in satellite location services. The conventional addressing system has less accuracy, and soon it will become inadequate in the era of Autonomous Vehicles and Delivery Drones.
The street address does not help guide an individual or machine towards a specific location such as building entrance, or parking or pick up spots. The conventional address system doesn’t help in identifying the precise location of an individual. A duplicate and similar street address sometimes create confusion in identifying the precise location, and a lot of times these errors go unnoticed in determining the correct address. Also, when a new building is developed, or a new street is opened for public, it takes time for the address to get registered in the current mapping system.
The current address systems are not accurate enough and employ a long combination of number and alphabets, which are easy to get wrong. The voice recognition system often makes mistakes in finding the right address. A new method needs to be identified to address the current challenge concerning location communication. The future technologies or businesses such as drone-based deliveries and autonomous vehicles will be compromised if the same address based location is employed in the future.
To address the challenges mentioned above, what3words Ltd has developed a matrix based solution to pinpoint the exact location of the address. The company has divided the world into squares of 3m x 3m, and each square is defined with a 3-word address such as rocky.silver.funded is the 3-word address for the specific location in Manhattan.
The company has created a unique solution to address the problem. The solution is based on the words. The company has employed only words in their algorithm because it is easy to remember as compared to the alphanumeric codes; this will further help to avoid mistakes. In addition, the auto-suggest feature provided by the company helps to guide to the user by what he/she meant. The system developed by the company is available in 22 native languages. The company has assigned a unique random name to 57 trillion tiles on the world map.
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The automotive industry is witnessing the progression at a rapid rate. The OEM’s such as Tesla, Audi, Nissan, and others are investing heavily in the autonomous vehicle development race. A car without a driver needs to have supreme accuracy concerning its direction. If the autonomous vehicle is not able to drop the passenger in the provided address, then the vehicle will face failure in the market. To make the autonomous vehicle a reality, there is a need to change the data that we are currently using. Location and identification of the correct location will act as the catalyst for the successful implementation of autonomous technology.
What3words has designed an algorithm to generate a random three words combination based on the GPS. The company has made similar sounding words geographically apart. This particular way helps both human and machine to identify the error incorrect time. The company has approximately employed 40,000 English words to cover all the tiles.
The urbanization is increasing its proximity because of the growing number of people. A large number of people are staying in close proximity. The accurate location system will help to locate the address precisely. This will further boost the logistics business and future delivery business such as delivery by drones and autonomous vehicles in delivering the passenger or goods to correct address. Nigeria and Mongolia Postal department are currently using the concept developed by what3words Ltd. This location-based service will also help people stuck in a natural disaster. Automo believes that precise location services are the most important parameter for the growth of autonomous vehicle. The industry will witness similar solutions in the future and is also expected to be an industry standard in the medium to long term.
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Keywords: Navigation, Innovation, Drone / Autonomous Vehicle, Unmanned aerial vehicle, self-flying drones, Autonomous Aerial Vehicles, collision avoidance sensors, obstacle detection