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Introduction
Why build a Smart Vision Network?
Data Fuels Technological Advancement
Thanks to advances in technological innovation, there has never been a time in history where data pertaining to human activity and behavior has been so easily and quickly accessible. The desire and need for instant data has been the key driving force behind the Information Age. The internet, computer, smart phones, social media networks, podcasts, and email are all but a few examples.
The vast majority of current data pertaining to human activity and behavior is owned and controlled by governments and/or large corporations, and used for internal benefits and monetization. This creates many inefficiencies and duplication requirements as data is rarely shared freely between entities. The few get to dictate and have full control over if and when the many may gain access the data created by their own actions.
The Lack of Real World Data
Digital Data pertaining to online human activity is abundant. Technology firms track our every online movement in order to fully understand and anticipate our needs and desires and to offer more streamlined and relevant solutions.
Real world behavioral data however, is lacking. The strong desire for this data can be witnessed by the existing sizeable market currently capitalizing on data approximations that are obtained from cell tower triangulation and cell phone tracking, both of which are on the decline due to privacy violations. Trillion dollar industries are reliant on data that is not as accurate as desired. Still, the demand is so high that an entire industry revolves around these sales. Apple’s recent privacy update requiring users to give permission for apps to track them has made a significant impact and has drastically reduced available sample sizes, making the available data even more inaccurate.
The significant infrastructure and resource costs required to build a network capable of capturing and digitizing outdoor activity in public areas, as well as the processing and analyzing of subsequent data in order to then make it useful has encumbered growth in this market. Costly workarounds are often used, such as cities sending engineers to manually count traffic in order to verify traffic complaints or verify expansion needs.
Certain well funded cities wishing to become “smart” have invested heavily in order to retrieve the data they seek, however in doing so, have often found the creation of more problems than solutions. Once the infrastructure has been put in place, and data acquired, the resources needed to enable solutions around the data has shown to be a significant challenge in itself. Investing in proprietary solutions that do not allow or reward outside parties to offer solutions has proven unfruitful and is a large part of the reason cities have drastically cut their infrastructure budgets; and companies like Cisco have pulled out of the smart city space after billions were invested.
Cities around the world are regularly challenged to provide better quality and more sustainable services, improve public safety, address congestion and environmental issues, all while reducing costs. Scaling existing infrastructure and human resource-intensive processes is difficult, expensive, unmanageable, and unsupportable for most cities with limited budgets. This problem is not specific to cities, the same applies to several other industries and markets.
Last modified 6d ago