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Sensors

The use of sensors is an increasing part of novel farming technology. Feeding back data for analysis on a wide range of different areas, both for plant and animal monitoring and analysis of behaviour in different environments. Supporting the evolution of modern farming techniques, at Agri-EPI we explore and deliver precision farming engineering, technology and innovation in UK agriculture across soil, crops and livestock.

International Day of Mathematics

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Happy International Day of Mathematics! Mathematics plays a significant role in agricultural technology in several ways:

  1. Modeling crop growth: Mathematical models are used to simulate the growth of crops. These models use mathematical equations to represent the different factors that affect crop growth, such as temperature, rainfall, soil nutrients, and pests. By using these models, farmers can predict how their crops will grow under different conditions and make informed decisions about when to plant, irrigate, fertilise, and harvest.
  2. Precision agriculture: In precision agriculture, farmers use technology to apply inputs (such as water, fertiliser, and pesticides) precisely where they are needed. This technique relies heavily on mathematical models, data analytics, and sensors to measure and monitor different parameters, such as soil moisture, nutrient levels, and pest populations.
  3. Farm management: Farmers need to keep track of a lot of data, such as crop yields, soil characteristics, weather patterns, and market prices. Mathematical tools help them organise and analyse this data, make predictions, and optimise their operations.
  4. Genetics and breeding: Mathematics is also used in genetics and breeding to study the inheritance of traits and develop new varieties of crops that are more productive, disease-resistant, and climate-tolerant. Mathematical models can help researchers identify the genes that control these traits, predict the outcomes of different breeding strategies, and optimise the selection of new varieties.

Overall, mathematics is an essential tool in agricultural technology, helping farmers and researchers make informed decisions and optimise their operations to meet the growing demand for food in a sustainable way.

Over the last months Agri-EPI has invested in the expansion of its team focused on data, engineering, and math, bringing on several new members and enabling them to offer a set of services to assist in the creation of agri-tech products.

Eliot Dixon, Head of Engineering, said:

“The team of platform and spectral imaging experts uses our fleet of sensors and specialist software to deliver a range of sensing products such as ground truthing for AI model generation, or the creation of digital twins. We are also now able to offer UAV and UGV platforms as a means to test novel sensors and end-effectors without the need for a bespoke vehicle. And through working closely with our innovation farm network, we are creating a heavily layered source of evidence for developers using our farm network to design and test their innovations.”

Agri-EPI’s GIS Data Analyst, Yingwang Gao, majored in Agricultural Engineering, and has a PhD degree specialising in Hyperspectral Imaging Applications, as well as postdoc experience working as Research Associate. In addition to a strong academic background, he has accumulated several years of industrial work experience, mainly on spectral imaging systems, R&D, and spectral imaging data analysis in various application domains. He has a strong passion for remote sensing and photogrammetry. At Agri-EPI, he takes care of data acquisition and data processing from different types of sensors, including RGB, multispectral, hyperspectral, LiDAR, and GPR, to identify and map out features of interest in the agricultural sector, to help farmers with better decision-making in agricultural management.

Agri-EPI’s new R&D Equipment Technician, Aditya Jadhav, pursued his bachelors in aeronautical engineering, where he learned various aspects of flying machines. He set up an aeromodelling club with a few of his classmates where they designed, built and tested various configurations of small UAVs. The MSc program for Autonomous vehicle dynamics and control was structured for students to gain a deeper understanding of unmanned systems. Aditya was part of a group project that built a surveillance system with a swarm of autonomous drones, and an individual project sponsored by the Railway Safety and Standards Board which aimed to design and develop an autonomous vehicle which can operate in a station environment. The advancements in robotics and the urgent need of integrating robotics with sustainable agriculture were the driving forces for him deciding to work in the agri-tech sector. As the R&D Equipment Technician, Aditya looks after all the deployable assets that are in service to the company, which includes maintenance, asset tracking and deployment, and organising the logistics.

Panagis Tzivras, Agri-EPI’S GIS Software Engineer, is a GIS expert with strong technical skills who is highly invested in programming. In his previous roles working with startups and the commercial sector, he was involved in data collection and extraction, maintaining data pipelines and building geospatial processes and automation updates. At Agri-EPI Centre he is helping to leverage the measurement resources of the centre to create high quality dataset and support systems. He is working on creating tools and code to enable the automation of data collection from a wide variety of sources available to Agri-EPI Centre.

Lastly, Aidan Robertson has joined the Agri-EPI Engineering team as their new Graduate Data Analyst. Aidan’s background is in mathematics, which he studied at University of Warwick for four years before looking for jobs related to data science. He has been working on projects related to the health and wellbeing of cows, specifically by reformatting farm datasets to be sent out for analysis. Soon, there are plans for him to begin a more ambitious project to develop a costings estimator for RAS in agriculture. This is a long-term task, but the ultimate goal would be to offer it as a service for farmers looking to introduce robotic systems into their farms. The most interesting part of agri-tech for Aidan is the data, and what it actually says about the performance of a system, as well as what can be done to help the problems being faced by the agri-tech sector at present.

 

 

Agri-EPI’s Farm Tech Circle

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Last summer Agri-EPI Centre launched the Farm Tech Circle, a new platform for farmers, growers and producers to discover and connect on topics that focus on enhancing the profitability and sustainability of agriculture.​ 
To learn more and to share this new network with members of the farming community who you think would like to be kept up to date with the latest news in agri-tech, please see below:

Farm Tech Circle

 

FTC Newsletter 1

FTC Newsletter 2

FTC Newsletter 3

Collaboration essential for successful agri-robotics

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By: Eliot Dixon, Head of Engineering at Agri-EPI Centre

Robotics has several strong applications in agriculture, especially in scenarios where systems can enhance the productivity of a shrinking workforce or can offer production efficiencies to the farm. However, to be successful in these applications the systems created need be reliable, in terms of long-term physical robustness but also in the ability of their control software to handle the very wide variety of scenarios they will encounter in a farming environment. This means the robots must be both well designed and well tested to meet the needs of farmers. This includes a design which emphasises safety and reliability.

“Understanding user requirements and testing in-field is key”

Good design requires a deep understanding of the needs and requirements of farmers and their farming systems. This extends from the core values held by a farmer, such as safety, which dictate their decisions; through to very specific requirements created by the unique combination of their way of working and the land they work. If this understanding is not achieved for a farming system, then there is a very high chance that the eventual product will be unsuitable, either creating a failed product or a long development timeline to solve the deficiencies. Gaining this understanding should come through working with a wide variety of farms within the target market for the technology, not just a small handful. In many agricultural sectors this design stage is especially important due to the limited testing season and ability to iterate on the design.

Testing is also well understood to be important to creating a reliable product, and in agriculture this does require a close collaboration with farmers to ensure that the robot meets their needs. As these are complex machines, which are also often dangerous if not created with a strong safety process, the testing regime should also be rigorous enough to ensure that the system will function to the desired reliability for all the design requirements. A rigorous testing regime would usually require multiple tests for each requirement across multiple operational scenarios such as different weather conditions, soil types, dangers, failure modes, crops etc. Failure to complete this testing will certainly result in the robotic system encountering situations which it is unable to function within, which may create unfortunate repercussions for the user or manufacturer. Unfortunately, completing this massive number of tests requires a range of test facilities, some of which might be beyond the capability of a company focussing on a small range of agricultural applications.

In our 2021 hackathon we explore safety and security. Outcomes are discussed in our white paper here:

Hackathon white paper

As mentioned, good design and testing is essential to creating successful products, but this unfortunately comes with a high cost. Doing this for the wide range of complex operating scenarios in UK agriculture, as well as the short testing cycles, is driving up the cost of developing agricultural robots. There are a multitude of Agri-robotics companies in the UK creating their systems from almost the ground up, each of which are individually bearing the cost in time and money of this development. This creates barriers to adoption in terms of high costs, a limited set of operations which can be conducted by robots, or low reliability due to poor engineering, and is increasing the amount of time it takes for products to get to market. As in all development the saying “Good, Cheap, Fast. Pick two”, is very much in action here but some very pressing needs mean we must find ways to break that deadlock.

Collaboration enables future opportunities for robotic systems

The obvious solution for this deadlock is to massively increase collaboration between ag-robotics developers. This has been proposed for many years, but we are yet to see a viable solution to this. Direct collaboration is currently difficult for commercial reasons with developers competing for the same money, but also for technical reasons where it is challenging to share components between robots. Perhaps a solution for this is to build an ecosystem of adaptable, compatible, components and platforms which can be used to create a multitude of agricultural robotic systems. This ecosystem of components would also be able to be robustly tested to ensure reliability when integrated as part of a larger system. Thus, the costs of development would be increasingly shared, without any single robotics manufacturer losing income as they are all developing for specific agricultural niches. Using a set of well proven components would allow developers to focus on ensuring good understanding and design for specific problems in agriculture, while also allowing for easier integration and testing of the robots.

Robotics in agriculture is a promising field, and with the right design and testing, as well as collaboration between developers, it could be a great success. By understanding the needs and requirements of farmers and using that to create an ecosystem of components and platforms, robots can be developed which are high value, robust, reliable and safe. With the right approach, agricultural robotics could benefit farmers across the UK and worldwide. Read our robotics and automation article to understand more about how we can support you to develop a robust well tested solution through collaborative R&D today.

Agri-EPI expands robotics and data offering

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Agri-EPI has developed its robotics and data offering, including the addition of 4 new members to their engineering team over the last couple of months.

Eliot Dixon, Head of Agri-Tech (Engineering) explains:

“Over the last few months Agri-EPI has been investing heavily in its engineering team, bringing on several new members, enabling us to offer a set of services to assist in the creation of agri-tech products. The team of platform and spectral imaging experts uses our fleet of sensors and specialist software to deliver a range of sensing products such as ground truthing for AI model generation, or the creation of digital twins. We are also now able to offer UAV and UGV platforms as a means to test novel sensors and end-effectors without the need for a bespoke vehicle. And through working closely with our innovation farm network, we are creating a heavily layered source of evidence for developers using our farm network to design and test their innovations.”

Agri-EPI’s new GIS Data Analyst, Yingwang Gao, majored in Agricultural Engineering, and has a PhD degree specialising in Hyperspectral Imaging Applications, as well as postdoc experience working as Research Associate. In addition to a strong academic background, he has accumulated several years of industrial work experience, mainly on spectral imaging systems, R&D, and spectral imaging data analysis in various application domains. He has a strong passion for remote sensing and photogrammetry. At Agri-EPI, he takes care of data acquisition and data processing from different types of sensors, including RGB, multispectral, hyperspectral, LiDAR, and GPR, to identify and map out features of interest in the agricultural sector, to help farmers with better decision-making in agricultural management.

Agri-EPI’s new R&D Equipment Technician, Aditya Jadhav, pursued his bachelors in aeronautical engineering, where he learned various aspects of flying machines. He set up an aeromodelling club with a few of his classmates where they designed, built and tested various configurations of small UAVs. The MSc program for Autonomous vehicle dynamics and control was structured for students to gain a deeper understanding of unmanned systems. Aditya was part of a group project that built a surveillance system with a swarm of autonomous drones, and an individual project sponsored by the Railway Safety and Standards Board which aimed to design and develop an autonomous vehicle which can operate in a station environment. The advancements in robotics and the urgent need of integrating robotics with sustainable agriculture were the driving forces for him deciding to work in the agri-tech sector. As the R&D Equipment Technician, Aditya looks after all the deployable assets that are in service to the company, which includes maintenance, asset tracking and deployment, and organising the logistics.

Panagis Tzivras, Agri-EPI’S new GIS Software Engineer, is a GIS expert with strong technical skills who is highly invested in programming. In his previous roles working with startups and the commercial sector, he was involved in data collection and extraction, maintaining data pipelines and building geospatial processes and automation updates. At Agri-EPI Centre he is helping to leverage the measurement resources of the centre to create high quality dataset and support systems. He is working on creating tools and code to enable the automation of data collection from a wide variety of sources available to Agri-EPI Centre.

Lastly, Aidan Robertson has joined the Agri-EPI Engineering team as their new Graduate Data Analyst. Aidan’s background is in mathematics, which he studied at University of Warwick for four years before looking for jobs related to data science. He is very pleased to be part of the Agri-EPI team in quite a varied role; so far, he has been working on projects related to the health and wellbeing of cows, specifically by reformatting farm datasets to be sent out for analysis. Soon, there are plans for him to begin a more ambitious project to develop a costings estimator for RAS in agriculture. This is a long-term task, but the ultimate goal would be to offer it as a service for farmers looking to introduce robotic systems into their farms. The most interesting part of agri-tech for Aidan is the data, and what it actually says about the performance of a system, as well as what can be done to help the problems being faced by the agri-tech sector at present.

Hyperspectral UAV

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Agri-EPI Centre has invested in the Hyperspectral UAV.

Compared to multispectral imagery, hyperspectral imagery measures energy in narrower and more numerous bands, thus giving much more information on target. Hyperspectral image data is 3D cube, where each pixel holds a full spectrum across the range. Since spectra are as unique as ‘fingerprints’ to target, hyperspectral imagery can unveil features that multispectral imagery may miss out on.

Hyperspectral imaging technology has been under research for decades and has been demonstrated to be very powerful in many application areas including agriculture. Especially in recent years, with a more robust and rugged imaging product embedded onto the UAV platform, agri-tech has seen revolutionary improvements.

The HySpex turnkey UAV solution with Mjolnir VS-620 and Lidar includes all the necessary hardware and software for flight planning, data collection, data processing and calibration. The system is provided with a UAV platform, 3-axis gimbal mount for the hyperspectral unit with Lidar and corresponding spectral calibration, radiometric calibration and geometric calibration. The geometric calibration includes a sensor model for VNIR and SWIR hyperspectral sensor heads, subpixel co-alignment of the 2 sensor heads, boresight calibration of the 2 sensor heads and internal IMU system, boresight calibration of the Lidar unit and internal IMU system.

There’s a broad application potential, including assisting in the development of products in the following application areas:
• Drought/water/nutrient stress monitoring
• Plant pathogens detection
• Analysis of soil properties/Determination of soil types
• Land mapping
• Yield forecasting
• Land management

UAV System (XQ-1400S BFD HySpex Edition):
1. <25 kg MTOW with Mjolnir and gimbal
2. Up to 25 min flight endurance with 8 kg payload
3. Fitted with high performance GNSS/GPS and IMU to enable data to be captured to high geolocation accuracy
4. Fitted with advanced 3-axis digital gimbal to compensate for the pitching

Sensing System (HySpex Mjolnir VS-620, Velodyne VLP-32C) :
1. Fully-integrated co-aligned hyperspectral visible and near-infrared (VNIR) and short-wave infrared (SWIR) (400 – 2500nm) and LiDAR sensors, along with in-flight data capture and storage system
2. Spectral coverage of 400 – 2500 nm, with spectral resolution of 3 nm in VNIR and 5.1 nm over SWIR range. Bit resolution 12bit in VNIR and 16 bit in SWIR.
3. Double resolution data in the VNIR range
4. High-resolution (0.33 degree) LiDAR sensor, with 360° surround view with real-time 3D data

They Hyperspectral UAV has potential use as groundtruth technology for other technologies/systems as well.

For information on renting out our technical assets please contact team@agri-epicentre.com

Multi-sensor VTOL UAV

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Agri-tech has undergone tremendous improvements with the introduction of remote sensing technologies, making many agricultural properties that were difficult to achieve before now accessible.

Multi-Spectral imaging has been widely used on satellites (e.g. Landsat) for earth observation science at a global scale. In the agricultural domain, UAVs as a platform have played a major role utilising various payload sensors including multi-spectral imaging.

The advantage of multi-spectral imaging is that it extends human sight sensitivity beyond the visible spectrum. Some wavelengths that are widely recognised for applications, such as the normalised difference vegetative index (NDVI), can be deployed into multi-spectral imaging. Nonetheless, it has been proved to be very useful in many other fields, greatly empowering the advancement of agriculture. The adoption of UAVs has made it possible to achieve large-scale mapping and thus better agricultural management.

Agri-EPI Centre has invested in the Multi-spectral VTOL UAV which has a potential use as ground truth technology for other technologies and/or systems.

This UAV and sensing payload system can also be used for a variety of fruit orchard use-cases which include:
• Estimation of leaf area index
• Estimation of canopy volume
• Estimation of water stress
• Fruit biomass estimation
• Temperature variation across the orchard
• Temperature variation of specific plants over time
• Fruit count estimation

It can also be used in other agricultural areas which include:
• Pest infestation detection
• Quantity moisture levels
• Analyse wildlife damage
• Vegetation index creation like NDVI
• Crop counting
• Create 3D photogrammetry maps

For information on renting out our technical assets please contact team@agri-epicentre.com.

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