CPS for Agriculture

Agriculture is facing some major challenges and CPS are expected to address some of them by contributing to smarter and more sustainable food production. A few applications already exist, but the extent to which farm management and processes will be automated and specific functions executed autonomously will increase as CPS technologies develop.

Summary

Agriculture is facing some major challenges and Cyber-Physical Systems (CPS) are expected to address some of them by contributing to smarter and more sustainable food production. A few applications already exist. The Internet of Things (linking the machines, interaction through data exchange, etc.) is starting to influence the agricultural sector to better support precision farming. The extent to which farm management and processes will be automated and specific functions executed autonomously will increase as CPS technologies develop. In the long term, beyond sensing technology and data collection, pattern recognition and artificial intelligence should improve the advanced interpretation of data and decision-making using data and domain knowledge. Fully autonomous machines (that establish, scout for pests, disease and weeds and care for, and harvest crops) might only be feasible at the very long term.

These developments will have profound impacts. Economically the European agricultural machinery industry could benefit from CPS. Some European engineering companies that have implemented these innovative technologies are doing very well, but the still more traditional machine builders have to make the switch to a more innovative company that implements the newest technologies. A number of high tech start-ups have introduced new technologies (such as apps, robots) in the agricultural sector. However, given the small economic margins of agricultural production, the cost price of agricultural technology can only be very low (which is not an stimulus for the development of advanced – and thus: expensive – new technologies).

Social impacts refer to safety, employment and skills. CPS might positively influence the quality-of-life of farm workers and also attract a younger generation back to farming. Robots might replace low and semi-skilled labour but existing farmers’ knowledge should be properly secured. Safety of robots is a main precondition for their market introduction in the agricultural sector. Also there is the question of who owns the data collected in the field (farmer, contractor). The implementation of new CPS technologies in agriculture can have considerable environmental impact leading to lower emissions, as well as reduced use of energy, water, chemicals and fertilisers. CPS can act as enabling technology in the development of more sustainable cropping systems. The combination ‘food and technology’ and especially ‘farm animals and technology’ is very sensitive. The introduction of new CPS technologies is expected to lead to ethical issues related to animal farming, the use of livestock robotics, and the relation between farmer and nature. The main legal issue that CPS raises in agriculture is the question of responsibility in case (autonomous) machines cause harm to persons, plants, animals or property.

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Introduction

Agriculture is facing some major challenges in the years to come. The world population is expected to grow to more than 9 billion people in 2050. Growing prosperity in developing economies is accompanied with changes in diet and an increased demand for food. This trend will be accompanied by a growing need for feed, fuel, fibres and chemicals. Options to mitigate these challenges are a more equal distribution of food and reduction of losses in the food chain (30-40% losses today), but also an increase in food production. The FAO indicates that food production has to increase by 60% to meet this growing demand (FAO Statistical Yearbook 2013). But there is more. The exhaustion of fossil fuels, fibres and chemicals will put more pressure on agricultural production. Resources like water, critical nutrients for crop production like phosphate show a declining availability (Pimentel et al., 2004; Schröder et al., 2010). Added to that, agriculture has a strong impact on the living environment through soil compaction and erosion, emissions of greenhouse gasses and the use of crop protecting chemicals and fertilisers. The use of medicines in livestock farming is related to a growing concern with respect to infectious animal diseases. As well, consumers continue to demand high-quality food for a low price, putting severe pressure on the agricultural farming business. All in all, these trends necessitate a more sustainable agricultural production, providing food, fuels, fibres and chemicals along with a healthy living environment for generations to come while assuring the livelihood of farmers who are facing the challenges of meeting these demands.

Agricultural technology is considered to be as old as agriculture itself (Evans, 1998; Mazoyer and Roudart, 2006). Breeding, agronomy, chemical fertilizers and chemical crop protection and antibiotics have all been critical success factors behind the considerable growth in agricultural yield over the past 10,000 years. And technology will continue to play a crucial role to address the challenges of a sustainable agricultural production.

Until recently, agricultural technology was mostly based on mechanical engineering. Many large, modern equipment manufacturers originate from local blacksmiths’ shop. Gradually, over the past 50 years, electronics, sensors, computing hardware and software, the Internet and wireless communications have entered the agricultural domain. They have evolved into systems that are indispensable for the agricultural production of today. This evolution of technology will continue, with advanced mechatronics, sensing, artificial intelligence and connectivity as key components. These technologies are expected to impact on future agricultural production and the food industry. They will enable machines, products and humans to interact with each other over the Internet and will lead to the development of (semi-) autonomous operating machines. These technologies – that can be considered to be part of Cyber-Physical Systems - are expected to bring agricultural a step further in the development of smarter and more sustainable farming.

In this paper we discuss several aspects of Cyber-Physical Systems CPS in future agriculture and in the food sector. We first describe the expected applications of CPS over the short term; in the next 5-10 years from now (2015). These are well predictable as they are often an extrapolation of what is now being developed. More uncertain are the applications of CPS on the long term; towards 2050. We will discuss what may be expected.

The technological developments of CPS technologies in agriculture and the food sector will have an impact on society, the economy and the environment. These impacts will be addressed in this paper. Furthermore, the political and legal effects as well as demographic developments with future CPS applications in the agro-food sector will be discussed. Future CPS applications will raise several ethical questions, which will be presented. Based on the overview of technological developments and their impacts, conclusions on future developments of CPS in the agro-food sector and its impact will be drawn.

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Conclusion

Cyber-Physical Systems will change the future of agriculture. The application of advanced sensors in combination with the Internet of Things and (semi-) autonomous robots can provide solutions to a number of problems facing the agricultural sector, including a declining work force and poor working conditions, while also achieving increasing production and optimising harvests. CPS in food production is expected to be incrementally implemented mainly for food safety purposes. In addition, CPS will allow for smarter food labels and packaging, providing richer information on all parts of the value chain.

The potential impacts are diverse and profound. Economically, the European agricultural machinery industry could benefit from CPS. Societal impacts encompass safety, employment and skills. Impacts in the legal domain include liability, data ownership and required modifications of the regulatory environment. The implementation of new CPS technologies in agriculture can also have considerable environmental impact leading to lower emissions, and reduced use of energy, water, chemicals and fertilisers. The combination ‘food and technology’ and especially ‘farm animals and technology’ is very sensitive and the introduction of new CPS technologies is expected to lead to many ethical issues.

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Societal impacts

The positioning of human labour is an important issue in the European agricultural sector (see also demographic aspects). Labour participation in the agricultural sector has decreased considerably: in the Netherlands in 1900 it was 30%, now it is 2.6%. This seems to be a global trend. When GDP increases, labour participation in agriculture decreases. Do people turn away from the sector because it is a low paid, dirty, physically demanding and involves long-working hours, or have machines taken over their jobs? The latter might be true as was the case for instance in 1830’s when increased mechanisation in agriculture, in this case the introduction of the threshing machine, led to societal unrest as many farmworkers were afraid to lose their jobs (see e.g. Griffin, C., 2012). However, one thing is clear: the number of farmers is declining. Small margins and high investments have not stimulated succession in family owned businesses (Landbouw Economisch Bericht, 2013).

In 2011, The Netherlands attempted to stimulate unemployed people to work in greenhouse horticulture. However, people were not motivated, did not have enough experience and work was considered to be too physically demanding. On the other hand the increasing use of technology might influence the daily life quality of farm workers and may also attract a younger generation back into farming (SPARC, 2015). In an automated farm, farmers can do their job on remote distance from the farm. In this context it is interesting to note that robotic milking systems in some cases are not cost effective, but are still adopted because the system buys time for the farmer to do other tasks on or outside the farm.

With respect to work skills, robots might replace low and semi-skilled labour in the future. Whether fully autonomous robots will enter agriculture with large numbers soon, is still a topic of debate. Blackmore (2012) does not expect autonomous robots in the long-term future. When robotics becomes more prevalent in agriculture, he expects that while agricultural robots will replace semi-skilled drivers, an equal number of high skill agricultural robots engineers will be needed to operate these advanced robots in the future. The SPARC Roadmap (2015) foresees a fully automated farm in which highly autonomous systems demand that the farmer accesses data only once or twice a day via the Internet to provide high-level supervision, allowing for “part time farming”.

The advent of CPS might have a negative effect on the body of knowledge embedded in the agricultural domain. When technology takes over, the ‘green fingers’ of the farmer might be lost. But do we need to understand the deeper workings of the engine when driving a car? Developments in technology do require that available farmers’ knowledge is properly secured.

Safety of robots is a main precondition for their market introduction in the agricultural sector. For industrial robots it may be sufficient to protect the work area or to exclude people from the working environment. In agriculture, there is direct physical interaction either with people, plants or livestock. In arable agriculture it deals with large and heavy machines work next to public areas, such as roads. This requires higher levels of safety which need to be embedded in the physical human machine interface. The SPARC report also mentions the issues of cooperation (behaviour of autonomous machines in natural environments that are not well-structured and have a complex layout) and organization (control in mixed environments, such as how to get a robot to the field and the driver back home) (SPARC, 2015).

Technological impacts

At the moment the main CPS-related technologies in agriculture involve sensors, combined with GPS and the Internet of Things. Sensors are used everywhere: on machinery, in the field, in animal houses, in greenhouses, in storage facilities, etc. Sensors are also playing a growing role in plant breeding as they objectively select the best cultivars based on predefined objectives.

Satellite observation of fields has a number of drawbacks (poor line of sight, clouds, etc.), and, for that reason, they are increasingly being replaced by observation by drones loaded with several types of sensors. Using the rich data these drones will collect it will be possible to better assess the status of the crop. In the short term, interpreting the data will largely be left to the farmer. They may, for example combine the data with world food prices and the cost of buying feed for cattle. The challenges of working with big data sets are in the analysis, storage, visualization and sharing of data as well as formulating good queries (SPARC, 2015). Given the growing availability of data, data mining is a rapidly developing field in agriculture (Mucherino et al., 2009; Liao et al., 2012; Bauckhage et al., 2013).

Also nowadays network technology and mobile communication have been already fully integrated into agriculture. Recently a huge rise of apps has been reported; for example one app is developed for detecting defects on machinery and providing instructions for repairs. Another helps with crop selection and harvesting. Also simulations and training programs for controlling machines are already widespread. In the coming years, apps will be increasingly used to analyse the land and soil and to link this information to local climatic conditions (measured by drones) (STT, 2015). An important key to future developments will be the interoperability and communication both between machines working on the farm and with organisations outside the farm in the post-harvest part of the value chain allowing faster processing of harvested crops, efficient transport and faster time to market.

The Internet of Things (linking the machines, interaction through data exchange, etc.) is starting to influence the agricultural sector; it is now being introduced and will steadily find an implementation in the next few years. Such connections will improve the processing of harvested crops, the efficiency of transport and the speed of time to market (SPARC, 2015). Interoperability requires standardization in how data is encoded and communicated through the production chain and between systems of different manufacturers.

By collecting data generated from GPS, drones, and sensors in the field and farming equipment, precision farming has enabled farmers to improve crop yields and water use, using advanced data analysis. Unlike in conventional agriculture, in precision farming the focus is on the specific need of a plant or animal (instead of a full field or herd). By responding to the specific conditions of the soil and climate, the harvest can be optimised. Data collection, analysis and intelligent decision making are essential to effectively carry out precision agriculture (STT, 2015).

Due to the remoteness of farming operations and the large number of livestock that could be monitored, the Internet of Things could revolutionize the way farmers work. It is expected that smart farming will become particularly important for predominantly agricultural-product exporting countries.

At the moment only a few robotic systems are commercially available. In livestock farming the milking robots have already been successfully introduced some decades ago. New products in livestock farming include automated feeding, manure removal, shed cleaning, and automatic field fencing. Horticulture (mainly glass houses with relatively high value added products) is the subsector where robots and advanced machinery are available for producing cuttings, planting in trays, plant protection, sorting and packing, essentially those activities that do not strongly rely on human intelligence or effective eye-hand coordination (Van Henten, 2006, 2013). Despite 30 years of research, harvesting robots are still not commercially available (Bac et al., 2014). There has, however, been much research activity in that field that may yield results in the medium to long-term. Examples are leaf picking of tomatoes (Tomation), sweet pepper harvesting, rose harvesting, sweet pepper packing, gripping of soft products, autonomous weed control, field robots and snack packing. Activities that strongly rely on advanced human skills are hard to automate. People still perform the non-robotised tasks of safety prevention and feedback on the quality of work performed by the robot.

A survey published in 2012, revealed that at that time there were no commercial products on the market (RoboNED, 2012). The past years have shown rapid development in this field and today, in arable farming, the first examples have entered the market demonstrating this technology can be applied to autonomous applications in agriculture.

The extent to which farming management tasks and processes can be automated will increase as CPS technology develops. More data collection and analysis using built-in domain knowledge of the specific characteristics of the farm will allow autonomy to increase gradually. At the moment it seems unfeasible to completely automate the data-driven management and operation in agriculture. The intelligence and skill of humans still largely exceeds the capabilities of the current technology. Though a vast amount of data is available, in the end, a decision has to be made about what to do. Giving the current status of technological development, it still are the farmers who decide as they have the most experience and expertise. They can decide quickly in complex situations. But real-time management information and knowing what to do is the key to successful and smarter farming and research will focus strongly on that aspect in years to come. Companies have not yet taken up the challenge of intelligent decision-making because mistakes might cause claims for liability for damages. Products are still mainly focussed on suitably visualizing available information. Visualisation and human machine interfacing are key themes.

Also in the post-harvest chain and food processing industry more and more semi-autonomous machines are doing the work, such as sorting and packaging of food products. Quality and product uniformity are drivers. Hygiene is an important driver for these developments given that humans are a potential entry point for contamination.

The main application of CPS in the post-harvest chain and food production is the use of sensors for food safety. A few examples of short-term applications of sensors in food production include: 1) intelligent packaging that can detect the level of freshness of a product; 2) millimetre wave sensors for contactless measuring of the core of a product for optimisation of freeze-drying processes in industry; 3) lab on a chip (several laboratory functions integrated on a chip of a few square centimetres) for diagnoses in diseased animals and 4) hyper-spectral cameras that can detect foreign objects, latent defects or fungi, and inspect the surface of products and a fibre optic biosensor for detection of (hidden) allergens, GMOs and DNA of microorganisms and viruses (STT, 2015).

In automotive, navigation systems, automatic braking and park assist systems are all features that prepare for fully autonomous driving in the long-term. Similar developments can be expected in agriculture. Human-machine collaboration is building a path toward autonomous farming systems.

The best estimate for long-term technological developments in this field is for the trends in research identified in the previous section to continue. Developments in sensor technology, for example are expected to continue. But beyond sensing technology and data collection, progress is expected in the field of pattern recognition and artificial intelligence for advanced interpretation of the data and decision-making using data and domain knowledge.

New technologies such as wireless communication, non-contact solid state sensors (phenotyping outdoor crops), Unmanned Ground Vehicles and Unmanned Aerial Vehicles are expected to contribute to advanced agricultural robots (Blackmore, 2012). However, it is hard to predict what levels of autonomy these robots will achieve in 2050.

The performance level and adoption of fully autonomous machines is still very low in agriculture, as was mentioned above. A number of problems encountered in arable agriculture and some also in (indoor) horticulture - might make that the introduction of fully autonomous machines for crop establishment, scouting and care and for selective harvesting will only be feasible at the long term. For arable land, these problems also include the size, compaction and trafficking (Blackmore, 2012). The large and heavy machines drive patterns that cover much more of the field area than is strictly necessary, damaging the soil (compaction). This also means that after heavy rain fall machines cannot enter the field. It was found that 90% of energy used in cultivation is for repairing the damages caused by machines. There is a big need for lighter machines that can work in wet weather conditions and do not damage the soil. These smaller machines are inherently safer for their environment than their larger counterparts. Challenges that still need to be addressed in general are: 1) intelligence, navigation and manipulation in unstructured environments (‘eye-hand coordination'); 2) fast decision making in complex situations, guaranteeing the safety for humans, animals and the crop; and 3) working in a hostile environment in terms of dust, dirt, rain, light, temperature variations, etc. (RoboNED, 2012; Bac et al., 2014). The SPARC Roadmap (2015) also mentions the development of multiple smaller machines rather than one large machine, which would reduce soil compression and be cost-effective even on very small fields. The overall reliability may also be higher.

It is expected that due to developments in the fields of sensor technology, information technology, and robotics, the application of precision farming will become more extensive. It will be increasingly possible to measure more accurately (at a distance) the requirements of a crop at a given time in a certain position allowing for further automation of farm operations such as land preparation and harvesting (STT, 2015).

As sensors allow for more data to be collected more quickly, this technology will contribute to further optimisation of food processing and quality control. It also provides (in conjunction with developments in genetic engineering) tools for structural improvements in the diagnostics and control of animal diseases as well as the development of more robust animals. In conjunction with micro- and nanotechnology, sensors can measure the specific composition of products for specific applications. For example, individual cows can be milked at the optimal point in their lactation, or fruits can be harvested when they hold fewer allergens. With sensor technology, animal behaviour can be observed in real time, allowing for more efficient farm management (STT 2015).

Smart materials on food labels, holding product information, can communicate with the whole production chain, allow for better registration and monitoring. Consumers can be better informed about what is in their food and where it comes from. Also the suppliers of fresh food products can trace the transport of these products and verify that they are delivered healthy and safely. Through interconnected IT systems (Internet of Things) the food packing can communicate with household kitchen machines. When smart labels are combined with smart packaging, data can be sent through the entire distribution chain, for instance refrigerators could make orders to the supermarket once a package indicates it is nearly empty. Or packages can communicate with televisions, which can be broadcast through targeted special offers. The smart packaging suppliers can learn more about their customers and make possible easier customisation. Finally, smart packaging could result in easier recycling of materials and prevention of food waste (STT, 2015).

Economic impacts

The value of agricultural machines produced in Europe is €28bn (30% of global production). Europe’s agricultural machinery industry consists of specialised manufacturers with a large variety of brands. Interoperability has been a long held tradition but with the advancement of CPS will become more challenging. Robotics in Europe has specialised in dairy while the US and Japan have specialised in high value crops (SPARC, 2015).

Considering the engineering strength of European manufacturers and high market shares worldwide, there is considerable potential for future development within Europe feeding a global market for autonomous agricultural machines (VDMA market research data, in SPARC, 2015). However, there is still a lot to gain for European companies. In order to do so, they have a lot to learn. Historically, the machine companies in agriculture are the local blacksmiths. Nowadays, software and ICT have become primary drivers of innovation and many more “traditional” companies have been slow to adapt. In contrast a number of high tech start-ups have introduced new technologies (such as apps or robotics) in the agricultural sector; some of these companies are doing very well.

Although farmers have a strong positive and innovative attitude towards robotics, the small number of companies that can afford such robots shows that there is hardly enough capital available to take the risk of developing and implementing high-tech robotic systems. As was stated in 2012, the risk for both farmers (growers) and suppliers in introducing new robot systems is in general unacceptably high. Government and R&D funding organizations do not support the developments in this field (RoboNED, 2012). The development of generic technological solutions that can be translated to specific solutions for individual crops and products might alleviate this issue. Current technical solutions are still too domain and application specific, thus yielding small markets and requiring large investments. Also, small scale robotic systems or modular CPS can provide small benefits. Then farmers can opt for a solution that meets their needs whilst being affordable. Adding modules should be possible when company development allows. Given the small economic margins of agricultural production, agriculture is a domain where requirements on technology are high but cost price of technology should be very low.

The SPARC report (2015) mentions the issue of ownership of data collected in the farm. The ownership of these data needs to be assured, as the data will be extremely valuable to third parties. Often farmers outsource activities to contractors (that own the machines). The same applies for the drones (which might also be owned by these or other contractors). Who is the owner of the data collected on the field or by the sensors in the animal houses; the farmer, the supplier of the drone/sensors, or the contractor that performs the measurements? Will drones be allowed to fly always, and above all fields?

A major driver for adoption of CPS and robotic systems is cost reduction. Statistics show that in The Netherlands over the last 30-40 years the share of income people have allocated to food declined from 25% to 10% (CBS data). The economic margins in agricultural production, being already small, are continuously under pressure and farmers will adopt technology to make ends meet.

It is worth noting that there might be a relation between scale enlargement of farms and the use of technology, though it is unclear whether scale enlargement calls for more technology or whether that scale enlargement provides the financial basis for the adoption of more technology.

Environmental impacts

Environmental challenges are drivers for introducing new CPS technologies in agriculture. They can lead to reduction of emissions, and more effective use of energy, water, chemicals and fertilisers. Precision farming offers the opportunity to provide water and fertilizers in an optimal fashion, both in space and time, thus yielding more efficient and effective use of scarce or expensive resources. Early and location specific detection and treatment of weeds, pests and diseases will reduce the use of crop protection chemicals and medicines, thus reducing a strong impact on the environment. While abstaining inputs of non-natural origin, robotics might offer a way to more widely implement organic farming. Potential tension between organic farming and high-tech may need to be investigated.

Another (local) environmental problem involves the large and heavy machines that destroy the soil structure (soil compaction). Large machinery was used mainly because of strong demand for high labour efficiency. Robotic technology allows a shift to small scale machinery. When more lightweight self-operating robots are available, the soil structure is less affected, thus contributing to a more sustainable agriculture.

The current working environment of agriculture might be too complex for current robotic technology (Bac et al., 2014). Modifications to crop production systems reduce complexity and facilitate the use of robotic technology. An example is the modified production system that was used for a robotic cucumber harvesting system (Van Henten, 2002). Similar developments are taking place with orchards. Novel cropping systems for apples alleviate both manual as well as future robotic systems for harvesting the apples. Robotic milking requires selection of cows for proper udder and teat configuration. “It may prove to be incumbent upon managers to assess udder and teat conformation before admitting a cow to the milking herd or to consider genetic selection for desirable teat placement, to avoid devoting labour to milking the anticipated 15% of the herd that will experience cluster attachment difficulties and failed milkings.” (Jacobs and Siegford, 2011). Breeding programs of plants and animals might also be directed towards facilitating robotic technology.

CPS in general and robotic systems in particular can also act as enabling technology for sustainable and environmental friendly agriculture. For example intercropping - i.e. cultivation of two or more crops in small rows in parallel, instead of monoculture - is known to have advantages from an agronomical and phytopathology point of view. In Western societies intercropping is currently unfeasible because it does not fit into the large scale farming machinery practices of today. Without robotic technology, the implementation of intercropping would be too costly. Small-scale robotic systems are better suited for such tasks.

Ethical impacts

The use of technology in agriculture and food supply touches upon a number of ethical issues. The first issue deals with the ethics of animal farming: every time technology touches living animals, ethical issues arise. Take, for instance, chickens on free-range farms. While free-range systems improve animal welfare versus cage systems, they present new challenges. Free-range chickens can lay their eggs anywhere, so farmers need to collect eggs by hand at regular intervals. A robot might take over this task. But what effect will robots have on the behaviour of chickens? Recent studies have shown that they did not have a negative effect (Usher et al., 2014). It is expected that such ethical questions will continue to be asked in animal farming.

The second issue deals with the use of advanced technologies in food production and which makes that the reality of food production in ‘factory farms’ does not match the romantic image that many people have of ‘family farms’ where inherently wholesome food are produced. Some authors consider agricultural farming as a form of industrial production (bio-industry) aimed at maximizing the use of raw materials, livestock, and resources and with negative impact for the environment (ICT-AGRI, 2012). The combination ‘food production and technology’ is very sensitive. There is some similarity with the GMO debate.

Although, the introduction of the milking robots was not a problem, there is increased interest in the ethics of livestock robotics. Recently the results of the study on the ethical issues related to the introduction of the milking robot in the Netherlands were published (Driessen and Heutinck, 2015). The study compared the use of a conventional milking apparatus with a milking robot. The study found that the entire practice of dairy farming has been reorganised around the new milking robot. With a robot, cows must voluntarily present themselves to be milked, whereby an ethical norm of (individual) freedom for cows emerged together with this new technology. However, it has also had an impact on what is considered to be good farming, specifically on the relationship between farmer and cow. Similar research is being done in the UK.

The RoboNED (2012) report has an interesting commentary on the ‘human looks’ of an agricultural robot. It says that: “as the essential functions needed in an agricultural robot comprise a limited subset of human capabilities, an agricultural robot need not resemble a human being”.

The increased introduction of the Internet of Things, through which packed and labelled food products communicate with kitchen and other household equipment, can have a considerable influence on the consumer’s daily life. Information about (un)healthy foods can be used to advise the consumer that want to change their eating habits. Food producers can also target consumers with tailored advertisement, etc. Information could be combined with input from consumers through social networking sites to ensure that tracking and tracing of products is much more accurate. Sceptics fear the consequences for privacy, and wonder whether it would still be possible to go 'off the grid' (STT, 2015).

In the old days, small-scale farming allowed for more specific individual attention to plants and animals. Mainly cost efficiency has led to large scale farming in which the distance between farmer and nature has increased. CPS might offer a way to meet the individual needs of plants and animals, though there will be a technical interface between farmer and plant/animal to implement this in a resource effective way. CPS might make the farmer’s lives easier in meeting individual demands of plants and animals. Alternatively, through CPS demands of the plants and animals will be more directly communicated, farmers might become ‘slaves’ of their crop or herd. This is an open and intriguing issue. Whichever way it goes, the relationship between farmer and nature will change

The Digital Divide, or the digital split, refers to the social exclusion faced by those without access to the Internet (especially broadband access). The lack of access prevents those on the wrong side of the divide from fully participating in an increasingly digitized society. The term became popular among concerned parties, such as scholars, policy makers, and advocacy groups, in the late 1990s. Similar issues might arise with advancing developments in CPS technologies. This not only holds for a separation between those who have and those who have not CPS in developed economies. It may also reinforce disparities between developed and developing economies as well. It is worth noting that the adoption of mobile phone technology in African countries has become widespread the past decade, indicating that new technologies are introduced and rapidly adopted in developing economies but with shape and cost that fits the local conditions. As such CPS will not be similar all around the world, adaptive technology needs to be developed to fit local requirements and conditions.

Demographic impacts

The composition of the work force in agriculture is a problem because it is relatively much older than in the rest of the economy (EU, 2013). Aging is a problem as these older workers will have to be replaced by younger workers, but these cohorts (ages between 25 and 45 years) are getting smaller and smaller. This trend, combined with the fact that there is already pressure on labour participation in agriculture (see Section 5), might have dramatic consequences for the European agricultural sector. The use of robotics on a larger scale would contribute to a solution. Robots also could take over the dangerous, heavy or unhealthy work in agriculture (STT, 2015).

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