The agriculture technology-as-a-service market has witnessed a heavy influx of technologies with the growth in the practice of precision agriculture. The market includes a set of technologies, for instance guidance technologies such as auto-steering systems and GNSS services, sensing technologies such as remote sensing, ground sensors, and aerial imagery, variable rate application technologies such as application control systems, flow control systems, precision applications system services, and data analytics and intelligence services such as machine learning platforms and farm management software. These technologies can also be referred to as component level technologies which are combined in different proportions in the market to offer advanced solutions such as agriculture robots and agriculture drones.

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Agriculture Robot-as-a-Service (ARaaS)

Precision agriculture practices and smart farming technologies have brought a new wave of modern agricultural equipment. Agricultural robots are an integral part of these next-generation equipment. However, the introduction of new equipment based on emerging technologies has escalated the expenditure for growers which they incur for profitable agriculture production. Planning to possess an agricultural robot for either of farming practices such as harvesting, weeding, pruning, or picking, puts an immense pressure of large capital expenditure and upfront costs on the growers. The burden becomes heavier on growers from emerging economies of Asia, Africa, and Eastern Europe. Moreover, another market restraint for agricultural robots is lack of technical awareness among farmers about
smart farming technologies. These factors combine to make growers hugely reluctant on planning to possess this modern equipment. This looming concern has been one of the major reasons behind the inception of the business model, Agriculture Robot-as-a-Service (ARaaS) among companies across the world. The continuous pressure on agricultural robot companies to maintain margin while maximizing adoption leads to their widening search for market opportunities beyond Agriculture Robotas-a-Service (ARaaP) model i.e., the one-time purchase model. ARaaS business model provides them this flexibility.

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ARaaS business model also allows the companies to take their agricultural robots into the market during the process of perfecting the product’s reliability. This becomes possible because the robots offered as a service will be operated by skilled operators who will be well equipped to deal with technical difficulties during operation. This way the companies also get field trial for their products along with customer feedback. This approach also allows operators to feed and store real-time farm data helping train machine vision algorithms and perfect the farm analytics software.

Largely, ARaaS model also has a limiting factor which eventually prompts companies to make a move toward following the ARaaP model. This limiting factor is majorly relevant for new and emerging companies which lack widespread global operations. ARaaS model is limited by the geographic position of the robots. Thus, until the customers are in the geographic reach of the ARaaS companies or the ARaaS company operators are ready to move to a world-wide scale to offer their services, this model would not be able to scale like in case of ARaaP model. Thus, ARaaP model is accepted in mature segments of agricultural robots such as milking robots, whereas ARaaS model is popularly adopted for the emerging segments such as weeding robots or harvesting robots.

Related Reports:

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Global Smart Farming Market – Analysis and Forecast (2018-2022)

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