‘IoT-ready’ Sensor Technology for

Connected Farms

http://scampp.com/

Krikor Ozanyan and Bruce Grieve

School of Electrical and Electronic Engineering

<K.Ozanyan@Manchester.ac.UK>; <B.Grieve@Manchester.ac. UK>

Sensors in 1st generation IoT

First wave: ‘All Data Are Sensed’

• Data acquisition

COTS sensors for basic measurands• miniaturisation

• low consumption circuits

• energy harvesting

• wireless-connected

• Data processing

Basic sensor fusion ‘tripod’• Architectures

• Algorithms

• Applications A

AA

http://www.gambica.org.uk/resourceLibrary/-the-internet-of-things-tree-of-life.html

Livestock farms - the supply chain

Food

Farm

Abattoir

Managing the chain -

essential for efficiency and resilience

• Upstream (e.g. food)• ingredients

• processing and storage

• formulation

• transport

• Downstream (e.g. abattoir)• transport

• schedule

• numbers/weight

Connected Farms in context: Improve food conversion

Food intake is accountable by volume/weight

Animal mass can be monitored by weight

• Food intake is regular• Animal weighing is much more challenging to manage

regularly and accurately• Existing weighing technology is either expensive and/or

o requires substantial maintenance; o requires staff engagement; o depends on manual/visual handling; o results in low throughput;o delivers raw data onlyo is difficult to connect

https://www.ritchie-d.co.uk

C‘OTS’ methodology needed

• Inexpensive, multiple weighing sites (100% covered)

• Allows regular weighing, as part of the farm routine

• Easy integration of animal ID (tags or camera)

• Unobtrusive for the animals

• Fully connected, upgradeable, re-programmable

• Low farm-floor maintenance, minimal disruption

?

Weighing - mature and widely spread, well commercialised For connected pig farms we need (at minimum overhead)

Borrowing iMAGiMAT™ technology

Translation to livestock farms: • Deployment in hostile environments – materials ‘sandwich’ to allow

reliable encapsulation without compromising sensitivity• Connectivity and flexibility (upgrading/re-programming)• Several application scenarios, based on sensing floor deformation

•New tomography type sensing, originally developed for human gait

•Based on deformation of plastic optical fibres, scales well in area

•Materials cost: ~£100 m-2

IEEE Sensors J. 15 (1) 279-289 (2015)

doi: 10.1109/JSEN.2014.2341455 .

Borrowing iMAGiMAT™ technology

Data acquisition• iMAGiMAT is based on collaborative sensor fusion from multiple POF sensors

arranged as a carefully designed grid in a single plane • No wires and no electrical currents under the mat, electronics at the periphery

Data processing• Imaging is by solving an inverse problem – special methods developed for

reconstruction at severe undersampling e.g. Hough transform.• Real-time reconstruction is speeded up by parallel computation in embedded

multiprocessor systems / FPGAs• Automatic decision making without visualisation – classifications by artificial

intelligence (deep neural networks)• Resources and communications efficiency is achieved by balancing “on-board”

and “hub” processing, as well as balancing real-time vs post-processing.

www.manchester.ac.uk/eee/e-agri

Agri-Food IoT, e.g. Above Crop Below Soil and beyond the Farm Gate

Sensors for protecting crop YIELD

● A sensor-network of 24/7 in-field disease pressure monitors

● Sensors “trick” pathogen into germination on mimic surface

● £2.5M leveraged funding, TSB Crop Protection competition

Sub-Soil Imaging

● New visualisation tool for seeds

breeders

● Tracks how efficiently the root

bundles are in drawing upon the

water and nutrients in the soil.

● An in-field tool for early isolation

and delivery of tomorrow's climate

tolerant food crops

Plastic Electronic-sensor Tagging (PET)

● UK, 4.1M tonnes of food that could have been

eaten is thrown away

● A technology platform for recording produce

temperature stress profiles from low cost,

battery-free, plastic RFIDs

● £1.5M leveraged funding from TSB Plastic

Electronics competition

N8 AgriFood – www.n8agrifood.ac.uk

One Network, Many Solutions

Multiuse Networked Platforms, e.g.IoT Crop “Tricorder” for < US$100

Connected GPS, camera, microprocessor

+Subtle light manipulation

= Active Close-Proximity Hyperspectral Imaging Fluorescence Imaging Stereo photometric Imaging Solid State Active Ellipsometry

Image courtesy of CBS Inc.

• Crop disease sensing• Early weed / plant detection;• Speciating insect disease-vectors;• Carbon footprint (protein in crops);• Leaf viral symptoms;

• Harvested fruit bruising & sugars• Soil organic carbon• Aquatic parasites• Frogs in salads ...

The near horizon

• Cloud – balance between data and information

• Big Data management, IoT+

• (C)OTS start – ‘bolt-on’ IoT capability necessary

• Standards – for modular structures where applicable

• People – education and training compatible with the spread and evolution of IoT