**6. Connecting smart agriculture, bioeconomy, and sustainable development**

In this chapter, we will present the analysis undertaken by the authors to determine possible contributions to sustainable development coming from modern approaches to smart agriculture and bioeconomy, based on the description of best practices in the Danube region. For this purpose, the well-known 17 sustainable development goals (SDG) proposed by the United Nations [20] are used as a reference frame. A qualitative description is presented in **Table 2**, and a quantitative approach, based on the binational expertise from Slovakia and Romania captured


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**UN SDG [20] No change Smart agriculture Full bioeconomy**

There will be no additional contribution in this respect

Agricultural runoff and resource usage will significantly decrease, improving water quality

Precision farming will generate more biomass and can also correlate with wind-/wave-based energy

People in the agricultural sector can move onto services or other advanced

Agriculture and supporting domains will gain an innovation boost to implement precision farms

Some minor improvement will ensue due to the commoditization of food

Rural communities will become smaller and more technologically advanced, while cities will receive better

An important component will be improved/reduced food and bioresources (e.g., fodder, raw materials)

The contribution of agriculture to climate change will be reduced through process optimization

ocean waters

will be reduced

Smart agriculture will reduce the ecological footprint upon

Improvements will take place in terms of food quality and availability, but job opportunities in agriculture

products

sectors

More improvements should happen consistently

All economic sectors will produce less waste, pollution, and runoff that affect water resources

There will be extra energy conservation by reusing processed materials and improving biomass yields

Bioeconomy requires renewed industries for horizontal and vertical

integration

Implementing bioeconomy will require considerable R&D effort in fundamental and applied sciences

Considerable entrepreneurship and innovation opportunities are to be expected

value chains

and reused

Additional connections within and among communities will be necessary to ensure new

In a bioeconomy model, most materials and components are recycled

Bioeconomy is one of the keys to addressing climate change, but other policy and technology measures are also needed

Agriculture and manufacturing have less impact, but transport and overfishing remain

Quality of life under bioeconomy is improved in all relevant areas: nutrition, health, future prospects, etc.

*DOI: http://dx.doi.org/10.5772/intechopen.86464*

The gender imbalance is changing slowly

Industry, agriculture, and transportation contribute to massive water quality problems

Fossil fuels play a major role in meeting the energy demands for economic development

Economic growth is slow and worker salaries tend to not be sufficient for decent living

Current trends can be maintained, with a broad and diverse focus of innovation

Income inequality among countries and inside countries is widespread

Current consumption patterns are unbalanced and affecting ecological balances

efforts

There are considerable difficulties in ensuring a balanced social and economic development

There are severe climate consequences to the current economic and industrial development

The health of the world oceans is severely affected by pollution and biodiversity reduction

The economic situation is still difficult for many countries and everyday life is affected for their

people

Goal 5: Gender equality

Goal 6: Clean water and sanitation

Goal 7: Affordable and clean energy

Goal 8: Decent work and economic growth

Goal 9: Industry, innovation, and infrastructure

Goal 10: Reduced inequality

Goal 11: Sustainable cities and communities

Goal 12: Responsible consumption and production

Goal 13: Climate action

Goal 14: Life below water

Goal 15: Life on

land


*International Cooperation for Smart and Sustainable Agriculture DOI: http://dx.doi.org/10.5772/intechopen.86464*

*Sustainability Assessment at the 21st Century*

devices, bearings, controllers, plugs, grease, paint, etc.).

be incorporated in the total preventive maintenance strategy.

Current economic models still have high levels of poverty and scarcity of resources

Hunger is still present in many locations on the globe due to economic and political factors

Existing

development models cannot keep up with population growth and increasing needs

Education is not given enough priority especially in terms of accessibility

**development**

Goal 1: No poverty

Goal 2: Zero hunger

Goal 3: Good health and well-being

Goal 4: Quality education

**6. Connecting smart agriculture, bioeconomy, and sustainable** 

In this chapter, we will present the analysis undertaken by the authors to determine possible contributions to sustainable development coming from modern approaches to smart agriculture and bioeconomy, based on the description of best practices in the Danube region. For this purpose, the well-known 17 sustainable development goals (SDG) proposed by the United Nations [20] are used as a reference frame. A qualitative description is presented in **Table 2**, and a quantitative approach, based on the binational expertise from Slovakia and Romania captured

**UN SDG [20] No change Smart agriculture Full bioeconomy**

Subsistence farming in developing economies will become more productive

Better yields will drive market prices down and will ensure better access to food

The need for chemical fertilizers and industrial farming techniques will be

Some improvements can come about but are rather

reduced

limited

Considerable impact across agriculture, manufacturing, recycling, and energy production

More abundant and more nutritious food will become available

Besides agriculture and food production, cosmetics and pharmaceuticals can benefit from bioeconomy

Considerable research and innovation are needed, and education will have to change to meet demands

considerable preventive maintenance in order to remain in an operating condition inside the environment of the silos, which is characterized by high amounts of dust, large variation of temperature with the outside weather, and possible blockages when grains enter the conveyor components and get lodged. The total preventive maintenance (TPM) model is applied with the help of two maintenance teams. A maintenance program is applied through software, based on a risk management algorithm that determines the components most prone to breakdown, taking into account complexity and history of operation. The software permits the grouping and scheduling of operations and the recording of maintenance dates, including tasks performed and situations encountered in the field, as well as the generation of material list for supplementing the consumables and materials stock (measuring

By implementing the smart conveyor instead of the classical version and by applying the total maintenance program on a silo with six conveyors (one for input and output from the building and five internal ones for moving and transporting the grains), the savings have been recorded to be over 6.5% of the total revenue per year, with a payback period of less than 3 years but an estimated active life (with proper maintenance) of cca. 15 years. **Figure 6** presents the main elements that can

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#### **Table 2.**

*Comparative analysis of sustainable development scenarios.*


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with the help of the Pugh method implemented in the Qualica QFD software, is displayed in **Figure 7**. Three scenarios are analyzed in parallel for a time frame of 11 years (2019–2030), with respect to the contribution in realizing the SGD: staying the current course with no significant change (basal scenario), implementation of smart agriculture/precision farming (realistic scenario), and full-scale implementation of bioeconomy including biotechnologies and bio-based industries (optimistic

This analysis served as basis for the implementation of a selection methodology known as Pugh's method that assigns weights to criteria (in our case the SDG) and ranks the alternatives based on neutral, negative, and positive effects. All the goals received a 5% importance rating, except three considered priorities that received 10% (hunger elimination, quality education, and climate action). The results are

As it can be noticed, the current course has a slow positive progression, the implementation of smart agriculture contributes significantly, but a full bioecon-

There is a significant potential for developing and implementing smart agriculture solutions in the Danube region, both in terms of policies and scientific contributions, and the elements presented in this chapter constitute building blocks of a proper ecosystem for this. Agriculture has historically been a strong sector for both Romania and Slovakia, and there are national policies as well as private initiatives attempting to recapture this competitive advantage in the form of smart devices, technologies, or projects. There is a good and diverse capability for developing this domain (strong IT sector, developed universities in the technical and life sciences areas, fast Internet, and good penetration of technology in rural areas), and we believe cooperation frameworks, like the Danube Transfer Centers Network and the Interreg-Danube projects, can contribute to transforming this capability through proper policies and instruments into concrete results. This is even more timely in the present with increasing discussion about possible food crises in the future, as well as an increasing focus on finding biological and ecological solutions for supporting a circular and sustainable industry, like growing fuels, construction materi-

omy approach on a world-wide scale would be much more effective.

als, and ingredients specific to the pharmaceuticals and cosmetics.

The international and transnational dimensions of cooperation in this sector come to complement the economic driving axis, because smaller countries that are cooperating in macro-regional (i.e., Danube region) or supranational (i.e., the European Union) contexts have improved chances of being competitive and developing fast in the current setting of a globalized economy. As proposed in the chapter, smart farming is only the first step in implementing a full-scale bioeconomy approach and should be undertaken soon to help change the status quo.

*DOI: http://dx.doi.org/10.5772/intechopen.86464*

scenario).

presented below:

**7. Conclusions**

#### **Figure 7.**

*Weighted comparison of scenarios—Pugh's method.*

### *International Cooperation for Smart and Sustainable Agriculture DOI: http://dx.doi.org/10.5772/intechopen.86464*

with the help of the Pugh method implemented in the Qualica QFD software, is displayed in **Figure 7**. Three scenarios are analyzed in parallel for a time frame of 11 years (2019–2030), with respect to the contribution in realizing the SGD: staying the current course with no significant change (basal scenario), implementation of smart agriculture/precision farming (realistic scenario), and full-scale implementation of bioeconomy including biotechnologies and bio-based industries (optimistic scenario).

This analysis served as basis for the implementation of a selection methodology known as Pugh's method that assigns weights to criteria (in our case the SDG) and ranks the alternatives based on neutral, negative, and positive effects. All the goals received a 5% importance rating, except three considered priorities that received 10% (hunger elimination, quality education, and climate action). The results are presented below:

As it can be noticed, the current course has a slow positive progression, the implementation of smart agriculture contributes significantly, but a full bioeconomy approach on a world-wide scale would be much more effective.
