General Overview and Problem
Last updated
Last updated
Today, mapping and geospatial data extend far beyond simple navigation. These technologies offer critical insights for efficient transport route planning, city zoning management, business strategy, and virtual exploration. Advancements in AI and sensor technology, such as cameras and LIDARs, allow maps to display dynamic, real-time information like road congestion, crowd sizes, and parking availability. This innovation paves the way for smart city and smart mobility applications, from crowd management to autonomous driving. The geospatial solutions market is projected to reach $845 billion by 2029, driven by these advancements.
Big tech companies have heavily invested in collecting map data, creating centralized data monopolies. These monopolies restrict access to essential geospatial data, impeding the map market's full potential.
Data Silos: Data sharing is crucial for innovation. Open geospatial data sharing could generate significant additional revenue. For example, the UK government estimates it could add $7 billion to $14 billion in new products and services.
High-Cost Burdens: Companies like Google have increased geospatial data prices drastically, leading to investigations for unfair practices. For instance, Google Maps' pricing increased over 1000% in 2018.
Unfair User Compensation: User data generates substantial revenue for tech giants. Google Maps is expected to earn over $11 billion in 2023 from user data. Analysts estimate individuals lose around $500 annually by providing their data, which may rise to $20,000 by 2034.
The future exacerbates these issues as mapping technologies gain more control. Autonomous cars and robots will make maps essential for both strategy and execution. A centralized entity like Google could dictate routes, influencing users under the guise of free will.
Cameras are ubiquitous, with 1 billion CCTV cameras and 44 billion cameras in mobile phones, drones, and cars globally. With AI and computer vision, these cameras can become "super sensors," detecting cars, humans, and events like traffic congestion at a lower cost than other sensors like LIDAR. However, using cameras raises privacy concerns and faces strict data privacy regulations, discouraging many companies from launching camera projects. Additionally, the cost of camera infrastructure is significant, with over $6 trillion spent on CCTV cameras globally, leading to potential data gaps due to maintenance issues.
Gps Network offers a solution by enabling users to upload videos of their surroundings, public places, and driving routes. Our AI analyzes these videos, rewarding users based on the quality and area of the content. This approach decentralizes data control and provides financial incentives, breaking data monopolies and empowering businesses and communities with real-time, locally-sourced geospatial data.
