# Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0
## 5 Future Perspective
* The maturity of 5 th generation (5G) technology is increasing the possibilities of automation of field processes and the acquisition of real-time information. During this 5 th industrial revolution, 5G is a substantial performer that has the potential, not only to facilitate high speed connectivity, but also faster data acquisition followed by analysis. For example, Google Earth, a free geolocation search engine, facilitates access to satellite imagery and integrates a processing code that could generate NDVI in turn [148], subsequently producing desired analytics in a mobile application or web-page. A practical example is the private company Graniot, operating in Spain [149]. Another interesting implementation of 5G could be the real time streaming of ultra-high definition images (4K-8K), taken by RPAs along with its potential to overcome the severe regulations on beyond visual line of sight (BVLOS) flight challenges. These tools are not limited to these kinds of applications, but rather to the unlimited opportunities. Further startups of this kind can help to achieve sustainable agriculture. * Masking all the data analyzing processes and protecting the end user, especially farmers, from the perplexity of technical processes in the form of graphical user interfaces (GUIs) could greatly boost the incorporation of these technologies among small-scale farmers. Only a limited number of studies have been reported where a user can visualize and interpret data in the form of mobile or tablet applications [150; 151; 152]. The invention of such types of GUIs can further ease sustainability and the profitability of the sector. * Benefiting from radio signals, television communication systems and cellular data are also appealing aspects of RS applications in rural areas. Another attractive option is the use of hotspot satellites for the determined range and area. RS technology is quite mature in developed countries, but, for developing countries, these tools can outweigh resource scarcity. * An anticipated model considering this 5 th revolution can be envisioned as one where data acquisition resources (e.g., sensors, RPAs, WSN, etc.) operate in synergy with field actors (e.g., tractors, AGVs, irrigation systems, spray systems, robots, etc.). Acquired crop data are then processed by cloud computing platforms, and ultimately generate insightful results. Thus, enabling the end user to interpret, make a reasoned decision or program a regulated activity through the corresponding GUI. Figure 9 shows this anticipated model. * The incorporation of RS technologies into agriculture can facilitate sector sustainability, but the associated costs could be a hindering factor. Today, most sensors applied in agriculture are quite expensive, along with the hiring of third party services for data interpretation. This is quite a big hurdle that need to be resolved. * Similarly, providing farmers with the basic skills needed for RS technology and training a fleet of young scientists can ease frustrations among people directly related to agriculture, like farmers, agronomists, extension workers, etc. The rate of adoption of a technology can be augmented using such measures. Private and public bodies can equally contribute to this sphere. * RS technology is no longer in its nascent phase and, therefore, a framework of proper vocabulary and standardization is urgently needed. Various terminologies are in use today that only create more confusion. An example of this problem is the naming of RPA technology--unmanned air vehicle (UAV) is the proper term for drones for few scientists, whereas others consider this term obsolete [7]. *Figure 8: Future considerations of remote sensing (RS) technology applied to agriculture. Figure 9: An anticipated model of remote sensing (RS) technologies applied to agriculture in the 5 th industrial revolution.