## 1 Introduction  
Surveillance systems have been evolving from simple local close-circuit television systems, aeronautical/aerospace systems [1, 2, 3], and integrated cities infrastructure systems [4] to complex military systems [5]. With the evolution of technology, the surveillance systems have become more powerful, with complex autonomous tasks delivered by Artificial Intelligence (AI) platforms [6]. Surveillance systems are sometimes wrongly associated to people behavior control protocols [7, 8]. The power of surveillance systems for fire control, infrastructure management, traffic control, assets managements, and others is indubitably valuable. A surveillance system over a large geographical area needs the support of a large data network infrastructure to interconnect several ground, sea, and aerial sensors to services that analyze its data. The network infrastructures are fundamental services of a society that are dependent on the continuous and proper functioning of a critical infrastructure network such as transportation, telecommunications, electric power, natural gas and oil, water distribution, economy, security, and quality of life [9]. These infrastructures are expensive, and the obstacles to its implementation limit its performance, functionality, and maintenance. By leveraging several Heterogeneous Smart Solutions (HSS) from several independent entities in the same infrastructure, private and public companies can share its costs. The same infrastructure can support several independent HSS as long as it guarantees its security, operability, independence, and performance. The goal and contribution of the presented Large Geographical Area Aerial Surveillance Systems Data Network Infrastructure is to offer such a system. Through employing AI integrated services, a reduction in the operability and maintenance costs is achieved. The AI growth in technology and solutions has been supported by investments from market leader corporations and governments. This is a solid indicator of its disruptive potential in the market. In 2019, the United States Government invested almost $5 billion in AI projects, including the $2 billion DARPA program [10]. China is showing a higher investment in AI R&D, with cities such as Shanghai and Tianjin investing $15 billion and $16 billion, respectively, in their AI industries over 10 years [10]. Other Chinese cities are following the investment in the AI innovation area. In 2017, China accounted for 48% of the global AI R&D funding [10]. Governments see a big strategic importance in the AI technology, leveraging large investments in its research. The European Commission is investing $1.7 billion for research and development, China alone is investing $47 billion, and Canada is investing $125 million in its AI strategy [10]. In 2016, $3.2 billion were invested in AI in Europe, and in the last 3 years, the European Union has funded $1.5 billion in AI research and innovation projects [11].  
By 2025, the world will see the shipment of 40 billion personal smart devices, and 90% of device users will have a smart digital assistant. Data utilization will reach 86%, and AI services will be readily available [12]. According to Huawei, AI becomes a new general-purpose technology and will change all industries and organizations [13].  
AI has the power to change almost everything about the way businesses operate and will contribute up to $15.7 trillion to the global economy by 2030 [14]. Of this, $6.6 trillion is likely to come from increased productivity and $9.1 trillion is likely to come from consumption side effects [14]. The global corporate investment in AI in 2015 was $12.8 trillion increasing to $67.9 trillion in 2020, including private investments, public offerings, M&A, and minority stakes [15]. Today, AI achieves 98.8% image recognition accuracy where humans only achieve 94.9%, as seen in the ImageNet Challenge Top-5 Accuracy created by Stanford University and Princeton University [15]. The ImageNet training cost has dropped from $1100 in 2017 to $7.43 in 2020 for 93% accuracy.