the future of agriculture - bootup · impact of big data across industries: big data – making...
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The future of agricultureTechnologies shaping the industry
Technology shifts impacting globalindustry Technology shifts in agricultureFuture of farming: Exploring the tractor segment Future of supply chains
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Technology shifts impacting global industry
Industries across the world today are being disrupted by the rapid spread of technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), Deep Learning and BigData.
Artificial Intelligence – a powerful change agent
By 2030, Artificial Intelligence is expected to add$15.7 trillion to the global economy.
What It IsAI is a branch of computer science concerned with creating independently cognitive intelligent machines. In a span of 60 years since the term was first coined, AI-based systems have demonstrated several impressive feats, including the ability to pilot a model helicopterand perform flying tricks at the level of world-champion pilots, after just a few hours of observation.
Industrial ImpactBy 2035, AI will contribute:
Industrial ImpactIndustries to be impacted by IoT include:
Internet of Things – connecting your world seamlessly
The industrial IoT opportunity could grow to$2 trillion by 2020.
What It IsIoT is an ecosystem of connected physical objects that are accessible through the internet. By 2019, IoT is expected to be double the size of the smartphone, PC, tablet, connected car and wearables market combined. According to Gartner, by 2020, there will be over 26 billion connected devices.
$12.2trillion to themanufacturing
industry
$9.3trillion to theprofessional
services industry
$8.4trillion to the
wholesale and retail industries
$4.6trillion to the
financial services industry
Energy management: Connected devices can sense movement and turn themselves on or off. This results in significant savings in electricity consumption.
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Media: IoT will induce better personalized and localized media consumption, based on device, geographic and socio-economic data.
Manufacturing: Biggest improvement areas include asset and situation management, network control, and management of the manufacturing equipment process.
Environmental monitoring: Get round-the-clock insights on soil, air and water conditions and alerts in case of anomalies or quality dips.
Deep Learning – Mimicking the way our brains process information
What It IsDeep Learning is part of a broader family of machine learning methods based on learning data representations. In Deep Learning, models inspired by how our brain works are expressed mathematically, and the parameters defining the mathematical models, which can be in the order of few thousands to 100+ million, are learned automatically from the data.
Industrial ImpactSome industrial applications of Deep Learning:
Industrial ImpactImpact of Big Data across industries:
Big Data – Making sense of the world through data
According to the Business Software Alliance (BSA), Big Data could have a $15 trillion impact on global GDP by 2030.
What It Is'Big Data' is a term used to describe a collection of data that is huge in size and yet growing exponentially with time. For instance,
- The New York Stock Exchange generates about 1TB of new trade data per day
- 500+TB of new data gets ingested into the databases of Facebook every day
- 10+TB of data is what a jet engine can generate in just 30 minutes of flight time.
Banking: Banks that have shifted their focus to ‘big data’ and ‘analytics’ consecutively have seen their annual revenue increase by 17 – 19%..
Healthcare: Big Data in the healthcare industry contributes 7% of market share in terms of revenue. By 2020, it is expected to be the third largest industry in terms of marketshare.
Medicine – Applications include radiology, pathology and dermatology.
Satellite imagery - For agriculture, intelligence and mapping
Robotics – Creating visual analysis ability in robots can positively influence areas like self-driving cars or machines that can automatically
Retail: A 60% improvement in operating margins and a 15 – 20% improvement in marketing potential is expected through using Big Data in retail.
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Why deep learning
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Technology shifts in agriculture
Agriculture is a $7.8 trillion industry, representing 10%of the world’s GDP,and employing over1.3 billion people, close to 40% of the global working population.As recently as 2010, there were only around 20 companies involved in agtech. But by 2015, the number had risen to 500+,with agtech financing reaching a massive$4.6 billionthe same year.
With the world’s population projected to reach 9 billion people by 2050, experts expect agricultural consumption to increase by nearly 70 percent over the same time. In addition, extreme weather events are on the rise, creating additional obstacles to productivity. The good news is that many technologies are coming together to revolutionizeagriculture in the face of these constraints.
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For AgricultureIoT sensors can provide farmers withinformation about crop yields, rainfall,pest infestation, and soil nutrition.
Smart farming also involves intensively controlled indoor growing methods.
IoT device installations in the agriculture world will increase from 30 million in 2015 to 75 million in2020.
Impact on farm machineryTractors can include IoT sensors, wireless communications, cloud apps and even steering-wheel replacements that guide precision passes across arable land.
A sensor can also measure the pressure being exerted on each seed as it’s planted. Thus, the seeds are set at the optimal depth for successful growth.
Technologies impacting agriculture
Internet of things
Drones
For AgricultureAgricultural drones can be miniaturefixed-wing airplanes, quadcopters ormultibladed small helicopters.
Crop imaging with a manned aircraft can cost up to $1,000 an hour. In contrast, farmers can buy drones for less than $1,000 each.
Drones - The new farm machine Drones have multiple farm applications. Some of these include:
- Soil and field analysis- Planting- Crop spraying- Crop monitoring- Irrigation- Health assessment
Robots
For AgricultureConventional tasks such as tilling, sowing and harvesting of grains canbe performed using autonomous robots with great accuracy.
The main area of application of robots in agriculture today is at theharvesting stage.
Application- Nursery planting- Crop seeding- Crop monitoring and analysis- Fertilizing and irrigation- Crop weeding and spraying- Thinning and pruning- Autonomous tractors- Picking and harvesting
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Future of farming: Exploring the tractor segment
From drone surveys to smart tractors to Uber for tractors, farming is expected to be revolutionizedin the coming future.
Self-driving tractors - To reduce manual labour and facilitate precision farming
Rising labour costs will bring about the adoption of automated process. High value crop are most likely to be early adapters of the disruption in autonomous technology. While John Deere has already launched driverless tractors, many players in the industry are working on technologies to turn existing tractors intosemi-autonomous machines. However, this will also require educating the traditional farmers to quickly adapt with the rising technology in farming.
- For agriculture suppliers, farm technologies could become a $240 billion market opportunity by 2030
- Small driverless tractors will independently contribute $45 billion to this market
- Automated tractors could lift farmer revenue by more than 10% while reducing labour costs.
- By 2050, autonomous vehicles, farm robots, drones, and high-tech agriculture equipment will result in farm yields rising by 70%.
- In countries like India, Nigeria, Ghana, Kenya, small businesses have already started for renting tractors and farming machinery.
- Smart tractors can increase the yield by 200% while cutting down land preparation time from 40 days to 8hours!
- Africa has less than 50 agricultural tractors per 100km² of arable land and hence Uberization of smart tractors is booming up.
-India being the largest among the developing countries, it is estimated to be INR 2500 Cr market by 2025.
- Tractor sales have dropped by 15% in the last one year in India.
Uber for tractors – Uberisatoin of tractors is already a thing in developing economies
As the world is moving towards the asset-free and asset-light business models, tractors and farm equipment too is no longer an exception to the trend. Farm machinery is costly, and formany small farmers in developing countries, even a simple tractor can be beyond their financial capacity. With rising maintenance cost and limited seasonal usage, it may not be the best option to own tractors and costly equipment.
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Impact of Online stores and Uberisation on Supply Chains:
Shared economy (Uber for X) and online availability of everything including spare- are putting unprecedented demands on the supply chain. Retailers are desperately searching for new supply chain and fulfilment solutions at every stage of operations, which includes demand forecasting, inventory management, warehousing strategies, technology integration, and distribution practices. In the omnichannel world, increasing demand through online stores has completely disrupted the traditional single channel supply chain.
- Almost 30% of all manufacturers have integrated their “traditional” supply chain processes with product and network design, manufacturing, and service.
- By the end of 2018, 60% of manufacturers will invest in cloud-based warehouse management systems and transportation management solutions aligned to their trade partner networks.
- By 2018, proliferation of advanced applications aligned to the IoT will result in 15% productivity improvements for manufacturing supply chains.
- By 2020, 50 percent of the operational jobs in the supply chain will haveevolved into “knowledge” roles required to support new technologies suchas cognitive computing and modern robotics.
- By 2022, 85% of the spare parts suppliers will use 3D printing
- By 2025, German spare part suppliers will save 3 Bn Euros by using 3D printing
Future of spare part logistics: 3D Printing
Making, storing, and shipping spare parts has always been a source of time-consuming and costly difficulties. Maintaining inventories of infrequently ordered parts is so expensive that suppliers often simply stop offering them. The advent of 3D printing, however, is about to change everything. 3D printing will enable suppliers to manufacture spare parts on an on-demand basis —and do so locally, close to where the parts are needed. Alternatively, companies can opt to print their own parts, bypassing the suppliers entirely.
Future of supply chains
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