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01Environment-independent cyber agriculture and intelligent farming

Technology-enabled, geographically dispersed, environmentally sustainable food production

Introduction

Agriculture today
Agriculture continues to profoundly impact our environment and resources as we cultivate, process and distribute across the planet. The challenge agriculture faces over the next few years is to feed a growing, increasingly urban population while dramatically decreasing its ecological footprint - in short, to grow more with less impact.

What will change
Emerging technologies such as connected sensors, machine learning and automation accelerate the development of a new kind of environment-independent agriculture. Instead of a global supply chain distributing mono crop harvests from distant farms, soil-free vertical farms dispersed throughout urban environments will shorten growing times and delivery distances while using a fraction of the land, water, and soil of traditional farms.

Emerging technologies to watch
Detective sensors will collect data from plants and feed this into systems monitoring production. This information will be collected from decentralised farms into centralised services that can learn from the results and share back learnings. Modern farming techniques such as aeroponics, aquaponics and hydroponics will mean crops can be grown anywhere, bringing production closer to populations and improving food security.

Opportunities to consider
9m2 of vertical farming produces harvests similar to 280m2 of horizontal farming at an astonishing yield rate of 95% - traditional farming averages a yield rate of 55%. These new approaches have the potential to meet food demands in all climates while shrinking land usage by 99% and using 95% less water. Corporate VCs such as Google Ventures & Softbank are already investing in this area. Technology and intelligent solutions will be an enormous business opportunity as the digitalisation of agriculture starts to accelerate.

Opportunities
  • Sustenance

    LED vertical farming units can enable locally automated food preparation, impacting production value and shortening supply chains.

  • Logistics

    Shorter supply chains shape logistics, pushing last mile deliveries.

  • Energy supply

    Distributed vertical farm networks will encourage localised renewable energy production.

  • Agriculture

    Early adopters of sustainable agriculture methods have the potential to impact food production across world markets.

  • Retail

    Retail value chains could shift as produce is locally grown and delivered directly to consumers.

  • Machinery

    Vertical farming smart machinery breakthroughs may have synergies with vertical warehousing. Similarly, indoor climate control, LED lighting and ventilation breakthroughs may have many cross-industry applications.

  • Built environment

    Urban smart cities can connect consumers’ homes and growing facilities to ensure harvests of right plants at the right time.

Deep-dive into this bet

Total market 2017

Agriculture market of around $ 12 trillion.

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Look for these 2024

Methodology: A high-level view gathered from various openly available data sources on market size & compound annual growth rates. To simplify comparison between analysts sources, we’ve removed differences in market details by calculating an estimated average for total market size 2024 and average CAGR for selected time period. This allows us to gain “correct enough estimates”. Unless linked directly to one source, each of our market estimate has included 2-8 sources e.g. WEF, CB Insights, Mordor Intelligence, Markets & Markets, Research & Markets, Grand View Research, PWC, Allied Market Research, McKinsey, Market Watch

1) Smart agriculture
$20,6 bn / CAGR: 15% (modern innovative technologies in soil analysis, crop management, cultivation and harvesting of crops)

2) Vertical farming
$8,6 bn / CAGR: 21% (aero, hydro, aquaponics including lighting, control, hardware)

Top 18 unicorn sniffing smart money VCs, 1376 investments 2018-2020

Source: Crunchbase Pro, accessed: 03/20, research of company description terms between 01/2018-02/2020, investment types: early stage investments by top 18 unicorn sniffing smart money VCs, n=1376 investments

3% of sustainability, 2% farming, and 7% biotechnology.

Special focus

Leveraging new hardware and software technology with sensors to monitor and automise optimal plant care-taking with fertilisers, light, air quality, and other parameters. Collaborating and competing with new players entering from surprising areas.

High capital and operating costs, vertical farming alone cannot solve all problems related to food production

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Initial investment, maintenance and labour are still high in costs as vertical farming is living it’s early days.

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Evergreen

Finland based, vertical farm solutions with the world's highest crop production per m2 and m3.

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Bowery Farming

Google Ventures invested $90 million in Series B round

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Plenty

Softbank has invested $200million in Series B

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Netled

Finland based, offers a turn-key solution - vertical farms with combined heat recovery system.

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Suomen Siemenperunakeskus (aeroponic potatoes)

Developed a way to grow aeroponic potatoes combining high tech and agriculture.

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Robben Vertikaalipuutarha

Finland-based mobile-controlled vertical farm, utilising Fujitsu sensor and remote control technologies. (contract value 2 million euros)

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Solar Foods

Solar Foods created a revolutionary way to produce natural protein by using renewable electricity and air.

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Lighting

LED (light-emitting diodes) lights enable adjusting the wavelengths to be suitable for different plants paving the way for profitable indoor farming. The next step in lighting will be lasers for plants, which are even more efficient than modern LED growth lights.

Cloud computing

Although cloud computing is nothing new its role will be redefined with the define its the advanced storage architecture that links cloud with edge.

AI/ML Artificial intelligence (AI)

Computer systems able to perform tasks normally requiring human intelligence by using a combination of Machine Learning (ML) toolbox of algorithms and learning rules from data.

Edge computing

A microcontroller unit (a small chip) is embedded with the ability to perform AI/ML computing offline based on sensor inputs without needing a cloud connection.

Computer vision

Using video image as a source for identifying, analysing and acting (objects & faces to provide access, personalise, charge, recommend, etc.)

Robotics

Both partially and wholly autonomous robots in applications such as logistics, storage, and iRRobondustrial settings. Robotics Automation could be used for harvesting and transporting plants in vertical farms, making it more safe for humans.

Indicators of change

Political

02 The full electrification
Get in touch with our team
  • Tuğberk Duman

    Business Consultant

    +358503266121

    tugberk.duman@futurice.com

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