The agriculture and food technology has dramatically evolved in the last decades, enhancing the productivity and the output of the industry as a whole. The explosion of Information and Communication Technologies disseminated in all areas of activity, agriculture included. Taking into consideration that the world population is constantly increasing, and agriculture has the mission to feed everyone, then the only way is to improve and find new ways to rise productions continuously.
New concepts like Smart Farming and Precision Agriculture have emerged. Smart Farming is a new stage of evolution that encapsulates the top information technology into the natural management cycle of the farm.

Precision Agriculture refers mainly to the temporal and spatial management to streamline economic results following a judicious deployment of resources while preserving the environment. It incorporates decision support systems, spatial images provided by drones, hyperspectral satellite images that contribute to the creation of maps displaying measurable variables like crop yield, topography, humidity, nitrogen levels, etc.
Ultimate technologies like Cloud Computing or Internet of Things are supposed to take the evolution even further and accommodate new robot features and computer artificial intelligence in new farming technology. Using Big Data, vast volumes of variable data, which is compiled and analyzed for decision-making, will be the norm.
Novelties like precision devices, geo-positioning systems, Big Data, Internet of Things, sensors, actuators, robotics or unmanned aerial vehicles will find their way to develop into the new modern technology used in agriculture.
Smart Farming is highly intercorrelated and connected to other agriculture modern technologies like management of information systems, robotics, and automation for agriculture and precision agriculture.
Smart Farming goes beyond just using in-field variability, it bases management operations on location and data, sharpen by context awareness, unleashed by real events. Real-time assistance features are very necessary to take agile actions, particularly in situations of emergency when operational conditions or circumstances modify tempestuously, like disease alert or weather changes. The technology englobes intelligent assistance in maintenance and implementation, adds autonomous context acknowledged devices, as sensors, built-in intelligence, which executes autonomous or remote tasks. Therefore, the human role will be involved more and more at the higher intelligence level, the execution of operational tasks being delegated to machines.
Smart Farming, in its further development, may pursue two extreme directions:
– Proprietary systems that are closed and within which the farmer will be integrant part of an integrated supply chain
– Collaborative systems that are open and within which the farmer has the flexibility to choose its partners and the relevant technologies
The future development of data and infrastructures, platforms, standards and their institutional implementation will incline the balance towards one scenario or another.
Smart Farming apps are not targeted just towards the large agricultural exploitations, but also can be implemented by small and common family farms to progress in their activity and earn more income. This approach is also welcomed from the environment point of view, as it helps optimize the water consumption, inputs and treatment procedures.
Hence, for now, the use of Smart Farming, in some form, touches about 80% in the USA and just about 24% in Europe, not to speak about the rest of the world. There is a long path to cover.
Consequently, the agriculture has to become smarter and Smart Farming is the way.