www.newelectronics.co.uk Open in urlscan Pro
20.107.224.27  Public Scan

Form analysis
1 forms found in the DOM

/search

<form action="/search" class="w-full flex">
  <div class="flex-grow">
    <label for="search" class="sr-only">Search</label>
    <div class="relative">
      <div class="absolute inset-y-0 left-0 pl-3 flex items-center pointer-events-none">
        <svg aria-hidden="true" class="h-5 w-5 text-gray-400" x-description="Heroicon name: solid/search" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 20 20" fill="currentColor">
          <path fill-rule="evenodd" d="M8 4a4 4 0 100 8 4 4 0 000-8zM2 8a6 6 0 1110.89 3.476l4.817 4.817a1 1 0 01-1.414 1.414l-4.816-4.816A6 6 0 012 8z" clip-rule="evenodd"></path>
        </svg>
      </div>
      <input id="search" x-ref="search" name="query"
        class="ml-[1px] block w-full pl-10 pr-3 py-2 border border-gray-300  leading-5 bg-gray-50 placeholder-gray-600 focus:outline-none focus:placeholder-gray-800 focus:ring-1 focus:ring-primary focus:border-primary text-sm sm:text-base"
        placeholder="What are you searching for?" type="search">
    </div>
  </div>
  <button type="submit"
    class="flex-shrink ml-3 inline-flex items-center px-4 py-2 border border-transparent text-base font-medium shadow-sm text-white bg-btn-primary hover:bg-btn-primary-dark focus:bg-btn-primary-dark focus:outline-none focus:ring-2 focus:ring-offset-2 focus:ring-primary leading-none">
    Search </button>
</form>

Text Content

Menu

   Topics
   
   
   TOPICS
   
   Board Level Design Displays Embedded Systems Internet of Things
   Optoelectronics RF & Microwave System Design
   Communications Hardware EDA & Design Software Embedded Software Memory
   Passive Components Research Design Test & Measurement
   Communications Software Electromechanical Interconnection Network Security
   Power Semiconductors Wireless Technology
   Sectors
   
   
   SECTORS
   
   Aerospace Consumer Distribution Medical & Healthcare Rail & Marine
   Automotive Defence & Security Manufacturing Policy & Business
   News
   
   
   NEWS
   
    * News
    * Videos
    * Events
   
   Features
   
   
   FEATURES
   
    * Interviews
    * Whitepapers
    * Outlook
    * All
    * Add your content
   
   Comment Supplier Network
   


 * SEARCH MENU
   
   Search
   
   Search



Share Facebook LinkedIn X Email

08 Aug 2024

More in

TECHNOLOGY

ARTIFICIAL INTELLIGENCE

INTERNET OF THINGS

SENSORS

WIRELESS TECHNOLOGY




HOW AI AND SENSOR TECHNOLOGIES ARE BOOSTING AGRICULTURAL PRODUCTIVITY

Features
6 mins read

Artificial intelligence (AI) is transforming industries worldwide, and
agriculture is no exception.


Credit: andriyyavor - adobe.stock.com

Monitoring every aspect of the growth cycle is essential. AI enhances and
optimises agricultural processes by providing real-time data analysis and
decision-making capabilities. By utilising soil sensors, humidity probes,
temperature sensors, light sensors, and imaging devices, AI can collect and
analyse critical data around environmental conditions and crop health. This
information enables farmers to make informed decisions about irrigation,
fertilisation, pest control, and other practices.

Used in conjunction with IoT communication solutions, growers can ensure
seamless integration and efficient operation of these technologies, creating a
more interconnected agricultural system.

Modern agriculture faces a complex interplay of environmental, technical, and
social challenges, all of which demand a cohesive and urgent response to ensure
resilient food production systems. As the global population continues to grow,
the demand for food is intensifying, exerting immense pressure on agricultural
systems to produce more with increasingly limited resources. One significant
hurdle is the loss of arable land to urbanisation and industrialisation.

Additionally, many farms still rely on outdated technologies, lacking the modern
tools necessary for optimising productivity and sustainability.

Social challenges compound these issues. The ageing population of farmers,
especially in rural areas, threatens the future of farming, as younger
generations are becoming reluctant to pursue agricultural careers. Small-scale
farmers and those in developing regions face additional obstacles, including
limited access to the resources and technologies needed to enhance their
practices.

Environmental challenges, including soil degradation, rising temperatures,
shifting precipitation patterns, and more frequent extreme weather events,
disrupt farming cycles and reduce crop yields. Soil degradation, driven by
over-farming, deforestation, and unsustainable practices, diminishes land
fertility. Additionally, biodiversity loss undermines ecosystem resilience,
making it harder for farms to withstand pests and diseases. The impact of both
natural and human-made disasters further increases these challenges. Floods,
droughts, wildfires, and storms can devastate crops, soil, and infrastructure,
leading to substantial economic losses and food insecurity.

Given these challenges, adopting sustainable and intelligent practices is
imperative. By leveraging technologies like AI and wireless connectivity, we can
enhance resource efficiency, improve crop yields, and promote environmental
stewardship. Embracing sustainability is essential for modern agriculture to
overcome these environmental, technical, and social challenges.

AI Utility Extends into Predictive Analysis

AI is reshaping agriculture, streamlining operations through sophisticated
cloud-based platforms, advanced analytics, and decision-support systems. It also
enables more sophisticated and targeted control at the edge.

AI facilitates the processing and analysis of data from myriad sensors across
farms, all centralised within the cloud. This integration offers a detailed,
real-time overview of agricultural conditions, blending weather, soil, and crop
data to furnish farmers with actionable insights for immediate application.

The utility of AI extends into predictive analytics, a cornerstone for modern
farming decision-making. By harnessing machine learning (ML) algorithms, AI
systems analyse data trends to forecast potential challenges and opportunities
within the agricultural cycle, such as pest infestations, disease outbreaks, and
the most favourable times for planting and harvesting. These predictive insights
enable farmers to pre-emptively tailor their irrigation, fertilisation, and pest
control strategies, improving both yield and resource efficiency.

AI is making a significant impact on agriculture by providing highly customised
decision support that can effectively direct farmers on how to farm a specific
field rather than relying on more generalised best practices. These AI-driven
systems amalgamate data from diverse sources, including weather patterns, soil
conditions, and market dynamics, to provide targeted recommendations. Platforms
like Climate FieldView use AI to offer tailored field-level insights and
recommendations for planting, spraying, and harvesting, enhancing the efficiency
of farming operations.

AI's influence also extends to environmental stewardship and land management.
Through sophisticated modelling techniques, AI aids in identifying and
implementing best practices for land restoration and sustainable management.
Tools like the LandPKS app leverage AI to combine GPS data, user inputs, and
extensive global databases, offering essential information on soil and climate
conditions. This supports not only sustainable agricultural practices but also
informed decision-making for landowners and environmentalists focused on land
conservation.

Moreover, AI, alongside ML, plays a crucial role in precision agriculture,
particularly in the variable-rate application of resources. By adjusting the
application of water, fertilisers, and pesticides based on the specific needs of
each field, AI-driven practices minimise waste and environmental impact,
elevating efficiency and reducing resource usage.

In essence, AI's integration into smart agriculture is transformative, enhancing
efficiency, sustainability, and the strategic use of data for informed
decision-making. Through its various applications, AI not only improves farm
management and yields but also supports the health of the planet, illustrating
the profound impact of technology on the future of farming.

The Role of Sensors for Creating Actionable Data

To impact agriculture, AI relies on a wide range of sensing technologies for the
vital data that is used to drive actionable outcomes. Supporting AI and ML
applications are a wide range of localised sensors to help collect continuous
environmental data, optimising irrigation and resource delivery.

A wide array of electrochemical and temperature sensors can be deployed to help
determine soil condition. Smart soil sensors, like Seeed Studio's MODBUS-RTU
RS485 Soil Sensor, offer combined sensing, providing an accurate indication of
soil temperature, moisture level, and composition. These devices can be used in
fields and greenhouses to continuously monitor soil and plant health. When
combined with AI technology, they enable the implementation of specific actions
to enhance plant well-being and minimise resource usage.

In addition to combined solutions, single sensor types are frequently utilised
to deliver precise feedback or to enable automations, such as automated window
opening in greenhouses or smart irrigation. Amphenol Advanced Sensors offers a
range of sensors designed to meet the demands of the latest expanding
agricultural applications, such as the Thermometrics T9501 (see below), which
features a water-resistant IP67 rating and enables farmers to monitor both air
and soil conditions accurately.



Amphenol Advanced Sensors Thermometrics T9501 humidity and temperature sensor.
(Source: Mouser Electronics)

To support the seamless integration of these technologies  FlexPIFA 6E antennas
ensure reliable data transmission between sensors and AI platforms. Designed for
harsh conditions, these antennas enable stable communication, ensuring
continuous data transmission to AI platforms for timely and accurate
decision-making.

Stationary sensors are not the only method for capturing farm data. Drones and
robots significantly enhance farming efficiency and sustainability. Equipped
with advanced cameras and sensors, drones monitor crop health, identify diseases
and pests, and assess growth patterns over large areas where localised sensors
are economically unviable. Drones like DJI's Agras also enable targeted delivery
of fertilisers and pesticides.

Similar to drones, autonomous robots are revolutionising farming by undertaking
tasks like seeding, weeding, and harvesting. These innovations automate
labour-intensive processes, improving accuracy and efficiency in crop
management. This technological shift has not only reduced the reliance on manual
labour but also promoted a more sustainable approach to farming by minimising
waste and chemical use.

Real-World Technology Integration

The agricultural industry is witnessing a transformation with the integration of
cutting-edge technology, resulting in both enhanced traditional machinery and
the creation of novel solutions that leverage innovations like edge AI, IoT
sensor networks, and ML algorithms.

With a hardware agnostic approach, Edge Impulse is a platform that enables the
development and deployment of high-performance AI models at the edge. One
example of their technology in action involved addressing over-irrigation by
deploying an ML-based solution.  Using an edge control board from Arduino with
temperature and humidity sensors, telemetry is collected, processed, and
analysed to optimise water usage.

The project employed local data storage and decentralised operation, achieving
high accuracy in determining irrigation needs and enhancing resource efficiency.
This demonstrated the viability of Edge Impulse’s solution in agricultural
applications.

Geospatial Data and AI Analytics

Geospatial data and AI analytics have significantly improved soil health and
crop yields. Satellite imagery and drones collect high-resolution images, which
AI algorithms analyse to create detailed maps of soil moisture, nutrient levels,
and crop health. Farmers use these maps to apply resources precisely, reducing
waste and enhancing productivity. Initial indications show that reduced amounts
of water and fertiliser are needed—anywhere from 20 percent to 40 percent less. 

Microsoft FarmBeats

Microsoft FarmBeats integrates IoT sensors with AI to monitor soil and weather
conditions. Sensors collect data on soil moisture, temperature, pH levels, and
weather, transmitting it to a cloud-based AI platform for real-time insights and
recommendations. The AI predicts optimal times for irrigation, planting, and
harvesting, helping farmers optimise water usage, improve crop health, and
increase productivity.

University of Illinois and John Deere Partnership

The University of Illinois and John Deere partnership develops advanced
agricultural equipment using AI and ML. They have created autonomous tractors
and robotic harvesters with AI-driven sensors and cameras. These machines
perform tasks like ploughing, planting, and harvesting with high precision,
adjusting operations based on real-time data. This has improved resource
efficiency and reduced labour costs, enhancing operational efficiency and crop
yields.    

Conclusion

AI is revolutionising agriculture by addressing the industry's environmental,
technical, and social challenges. Using cloud-based platforms, AI-powered
analytics, and advanced sensors, farmers can optimise their operations and
promote sustainability.

Engineers play a crucial role in developing and implementing these innovative AI
solutions, driving the future of smart agriculture and ensuring food security
for generations to come. As the agricultural sector continues to evolve, the
integration of AI and other advanced technologies will be essential for
overcoming the complex challenges faced by modern agriculture.

Author details: Mark Patrick, Director of Technical Content, EMEA, Mouser
Electronics

Artificial Intelligence
Agricultural Technology
Sensors
Internet of Things
http://www.mouser.com

COMMENTS


Please enable JavaScript to view the comments powered by Disqus.
RELATED ARTICLES

Artificial Intelligence


AGRICULTURE 4.0

Features
Wireless Technology


NOKIA AND VI CSR DEPLOY SMARTAGRI SOLUTION

News
System Design


FEED THE WORLD

Features
Sensors


AGRICULTURE DIGITALISATION

Features
Electronics


FARMING ON THE EDGE

Features
Manufacturing


IOT PLATFORM SUPPORTS PRECISION AGRICULTURE

News



LEGAL

 * Terms & Conditions
 * Privacy Policy
 * Cookie Policy
 * Reuse permissions


INFORMATION

 * Contact Us
 * About Us
 * Editorial
 * Advertising
 * Circulation


FREE ACCESS

 * Free access to this content is for qualifying individuals only. Corporate and
   institutional access requires an appropriate license or subscription. For
   more information contact institutions@markallengroup.com

© Copyright 2024 Mark Allen Group
 * Privacy policy
 * Cookie policy
 * Terms & conditions
 * Cookie Settings

✓
Thanks for sharing!
AddToAny
More…

×
This website uses cookies
This website uses cookies to improve user experience. Choose which cookies you
allow us to use. For more information, please review our Cookie Policy. Read
more
Save & Close
Accept Additional Cookies
Reject Additional Cookies
Show details Hide details

Strictly necessary

Performance

Targeting

Functionality

Unclassified
Cookie declaration
About cookies
Strictly necessary
Performance
Targeting
Functionality
Unclassified
Strictly necessary cookies allow core website functionality such as user login
and account management. The website cannot be used properly without strictly
necessary cookies.

Cookie report Name Provider / Domain Expiration Description AWSALBCORS
Amazon.com Inc.
markallengroup.blueconic.net 7 days For continued stickiness support with CORS
use cases after the Chromium update, we are creating additional stickiness
cookies for each of these duration-based stickiness features named AWSALBCORS
(ALB). CookieScriptConsent
CookieScript
.newelectronics.co.uk 6 months This cookie is used by Cookie-Script.com service
to remember visitor cookie consent preferences. It is necessary for
Cookie-Script.com cookie banner to work properly. AWSALBCORS
Amazon.com Inc.
m417.newelectronics.co.uk 7 days For continued stickiness support with CORS use
cases after the Chromium update, we are creating additional stickiness cookies
for each of these duration-based stickiness features named AWSALBCORS (ALB).
AWSALB
Amazon.com Inc.
m417.newelectronics.co.uk 7 days These cookies enable us to allocate server
traffic to make the user experience as smooth as possible. A so-called load
balancer is used to determine which server currently has the best availability.
The information generated cannot identify you as an individual.

Performance cookies are used to see how visitors use the website, eg. analytics
cookies. Those cookies cannot be used to directly identify a certain visitor.

Cookie report Name Provider / Domain Expiration Description _ga
Google LLC
.newelectronics.co.uk 1 year 1 month This cookie name is associated with Google
Universal Analytics - which is a significant update to Google's more commonly
used analytics service. This cookie is used to distinguish unique users by
assigning a randomly generated number as a client identifier. It is included in
each page request in a site and used to calculate visitor, session and campaign
data for the sites analytics reports. _gid
Google LLC
.newelectronics.co.uk 1 day This cookie is set by Google Analytics. It stores
and update a unique value for each page visited and is used to count and track
pageviews. _gat_UA-4663863-10 .newelectronics.co.uk 43 seconds This is a pattern
type cookie set by Google Analytics, where the pattern element on the name
contains the unique identity number of the account or website it relates to. It
is a variation of the _gat cookie which is used to limit the amount of data
recorded by Google on high traffic volume websites. _ga_YKDZ07XYCJ
.newelectronics.co.uk 1 year 1 month This cookie is used by Google Analytics to
persist session state.

Targeting cookies are used to identify visitors between different websites, eg.
content partners, banner networks. Those cookies may be used by companies to
build a profile of visitor interests or show relevant ads on other websites.

Cookie report Name Provider / Domain Expiration Description SRM_B
Microsoft Corporation
.c.bing.com 1 year This is a Microsoft MSN 1st party cookie that ensures the
proper functioning of this website. CLID www.clarity.ms 12 months 4 days This
cookie is usually set by Dstillery to enable sharing media content to social
media. It may also gather information on website visitors when they use social
media to share website content from the page visited. MUID
Microsoft Corporation
.clarity.ms 1 year This cookie is widely used my Microsoft as a unique user
identifier. It can be set by embedded microsoft scripts. Widely believed to sync
across many different Microsoft domains, allowing user tracking.
VISITOR_INFO1_LIVE
Google LLC
.youtube.com 5 months 29 days This cookie is set by Youtube to keep track of
user preferences for Youtube videos embedded in sites;it can also determine
whether the website visitor is using the new or old version of the Youtube
interface. YSC
Google LLC
.youtube.com Session This cookie is set by YouTube to track views of embedded
videos. MUID
Microsoft Corporation
.bing.com 1 year This cookie is widely used my Microsoft as a unique user
identifier. It can be set by embedded microsoft scripts. Widely believed to sync
across many different Microsoft domains, allowing user tracking. MR
Microsoft Corporation
.c.bing.com 6 days 23 hours This is a Microsoft MSN 1st party cookie which we
use to measure the use of the website for internal analytics. MR
Microsoft Corporation
.c.clarity.ms 7 days This is a Microsoft MSN 1st party cookie which we use to
measure the use of the website for internal analytics. SM .c.clarity.ms Session
This is a Microsoft MSN 1st party cookie which we use to measure the use of the
website for internal analytics. ANONCHK
Microsoft Corporation
.c.clarity.ms 10 minutes This cookie carries out information about how the end
user uses the website and any advertising that the end user may have seen before
visiting the said website.

Functionality cookies are used to remember visitor information on the website,
eg. language, timezone, enhanced content.

Unclassified cookies are cookies that do not belong to any other category or are
in the process of categorization.

Cookie report Name Provider / Domain Expiration Description _clck
.newelectronics.co.uk 12 months 4 days _clsk
Microsoft
.newelectronics.co.uk 1 day BCSessionID www.newelectronics.co.uk 1 year 1 month
.AspNetCore.Antiforgery.nixphHDAMN4 www.newelectronics.co.uk Session BCSessionID
m417.newelectronics.co.uk 1 year 1 month VISITOR_PRIVACY_METADATA
YouTube
.youtube.com 5 months 29 days .AspNetCore.Mvc.CookieTempDataProvider
shiningseasandbeautifultrees.com
www.newelectronics.co.uk Session BCSessionID markallengroup.blueconic.net 12
months 5 days __eoi .newelectronics.co.uk 5 months 29 days _clsk
Microsoft
www.newelectronics.co.uk 1 day

Cookies are small text files that are placed on your computer by websites that
you visit. Websites use cookies to help users navigate efficiently and perform
certain functions. Cookies that are required for the website to operate properly
are allowed to be set without your permission. All other cookies need to be
approved before they can be set in the browser.

You can change your consent to cookie usage at any time on our Privacy Policy
page.
Cookies consent ID:
Cookie report created by CookieScript