{"id":9130,"date":"2021-10-28T07:26:53","date_gmt":"2021-10-28T07:26:53","guid":{"rendered":"https:\/\/blog.cloudthat.com\/?p=9130"},"modified":"2024-06-25T11:06:45","modified_gmt":"2024-06-25T11:06:45","slug":"how-can-cloud-computing-help-farmers-increase-production-and-save-water-and-energy","status":"publish","type":"blog","link":"https:\/\/www.cloudthat.com\/resources\/blog\/how-can-cloud-computing-help-farmers-increase-production-and-save-water-and-energy","title":{"rendered":"How can Cloud Computing help farmers increase production and save water and energy?"},"content":{"rendered":"

Cutting Edge technologies\u00a0such as the Internet of Things (IoT), Artificial Intelligence (AI),\u00a0Machine Learning\u00a0(ML),\u00a0Computer\u00a0Vision, and\u00a0Cloud\u00a0Computing are assisting many industries in increasing production and expanding their business. In this blog, we will look at how these technologies can help farmers with things like farm monitoring and control, weather prediction, disease and pest management, and livestock tracking.<\/span><\/p>\n

In this blog, we can shed some light on leveraging technology to advance agricultural practices, reaping better produce.<\/p>\n

Table of Contents<\/h1>\n

1. Farm Monitoring\u00a0by IoT
\n<\/a>2. AI\/ML Based irrigation
\n<\/a>3. AI\/ML\/Computer-vision Based disease prediction\u00a0and\u00a0crop health analysis
\n<\/a>4. AWS IoT\u2019S cycle of\u00a0services
\n<\/a>5. IoT Case Studies and CloudThat’s offerings<\/a><\/p>\n

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Farm Monitoring\u00a0by IoT<\/h1>\n

Farm monitoring is simply understanding what the farm’s climate conditions are, such as temperature, humidity, wind speed, and other factors, as well as the farm’s state, such as pump status, water-valve status, and energy consumption.<\/span>\u00a0<\/span><\/p>\n

We can utilize temperature and humidity sensors, soil moisture sensors, soil temperature sensors, wind direction, wind speed, and rainfall sensors to monitor the\u00a0farm. Sensors\u00a0are connected to microcontrollers and other communication devices, which can be powered by batteries or solar panels.<\/span>\u00a0<\/span><\/p>\n

Two scenarios exist for sensor devices to connect with the cloud. One is that all gadgets will be connected to the internet and will send data to the cloud for processing. The other option is to use a gateway to transport all sensor data to the cloud. Both ways are used depending on the application.<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

\u00a0\"\"<\/a><\/span><\/p>\n

In the image above, you can see that the pump and actuator module\u00a0(microcontroller & relay)\u00a0are linked to the cloud via an internet connection made via GPRS\/LTE\/Wi-Fi\/NB-IoT. This stand-alone pump module can send data to the cloud at regular intervals via MQTT protocol (MQTT is a lightweight protocol that allows devices to communicate with one another via a publish-subscribe model). The\u00a0data will include pump on\/off status and energy consumption.\u00a0Data received in the cloud is then processed and stored in a database before being sent to the mobile application to be viewed by the user. The mobile app allows the user to turn on\/off the pump and set the running time interval based on the use case.<\/span>\u00a0<\/span><\/p>\n

\u00a0\"\"<\/a><\/span><\/p>\n

 <\/p>\n

In the diagram above, the Gateway serves as a link between the cloud and the edge devices. At the edge, IoT devices range from a few meters to kilometers, and these devices communicate with the gateway using various communication protocols such as Wi-Fi\/BLE for short-range (meters) and LoRa\/ZigBee for long-range (kilometers). The edge-node data is received by the gateway, which adds the token, if necessary, before sending it to the cloud. Tokens\u00a0help to find data corresponding to which edge IoT device. Further processing will take place in the cloud, and further data will be sent to the Mobile-APP\/Web\/Echo device as needed.<\/span>\u00a0<\/span><\/p>\n

AI\/ML Based Irrigation<\/h1>\n

We now have a plethora of weather APIs that can anticipate high-probability weather forecasts.\u00a0These\u00a0APIs are Application Programming Interfaces that give you global access to current and historical weather data.\u00a0<\/span>\u00a0<\/span><\/p>\n

We can anticipate the likelihood of rain falling at a specific place using this weather API, by which we can assist the farmer with irrigation planning.\u00a0<\/span>\u00a0<\/span><\/p>\n

For example, if the likelihood of rainfall next week is quite high, then the mobile app\u00a0can be used\u00a0to aid the farmer to do minimal irrigation instead of doing 100% irrigation. By conserving water and energy, farmers can ensure that their crops remain healthy by avoiding overwatering. This benefits the farmer by conserving water, energy, and the health of their\u00a0crops.<\/span>\u00a0<\/span><\/p>\n

\u00a0\"\"<\/a><\/span><\/p>\n

 <\/p>\n

We can collect sensor data such as temperature, humidity, soil moisture, and so on by using a local weather station located within the farm. Using this parameter, we can automate farm operations to assist farmers in conserving resources.<\/span>\u00a0<\/span><\/p>\n

AI\/ML\/Computer-vision Based disease prediction\u00a0and\u00a0crop health analysis<\/h1>\n

\u00a0 \u00a0 \u00a0 \u00a0\"\"<\/a><\/span><\/p>\n

Images of crops and plants will be captured using drones and cameras. And\u00a0this\u00a0data is sent to the cloud for further processing. With the use of AI\/ML and these crop pictures, we can discover crop sickness. We can advise the farmer in providing correct fertigation to the crops by forecasting plant disease.<\/span>\u00a0<\/span><\/p>\n

AWS IoT\u2019s cycle of\u00a0services<\/h1>\n

\u00a0<\/span>The\u00a0diagram\u00a0below\u00a0tells\u00a0us the different\u00a0services offered by AWS for different scenarios.<\/span>\u00a0<\/span><\/p>\n

\u00a0\"\"<\/a><\/span><\/p>\n

Device Services will assist edge devices and gateways in operating and connecting to the AWS cloud.\u00a0The devices’ security, control, and management are accomplished\u00a0through the use of\u00a0connectivity and control services.\u00a0Analysis\/AI\/ML services perform value extraction and analysis.\u00a0With the assistance of these services, one can create a fully automated IoT solution.<\/span>\u00a0<\/span><\/p>\n

This summarizes the application and benefit of using IoT in the field of agriculture and how to monitor various events using AWS IoT cycle of services.\u00a0Thus Internet of Things (IoT), Artificial Intelligence (AI) and Machine Learning,\u00a0Computer\u00a0Vision, and\u00a0Cloud\u00a0Computing can therefore\u00a0help farmers save water and energy\u00a0and\u00a0increase crop production.\u00a0<\/span>\u00a0<\/span><\/p>\n

IoT Case Studies and CloudThat’s offerings<\/h1>\n

CloudThat’s<\/a><\/strong> IoT team has successfully implemented AWS IoT Core Setup for various customers. Here is a case study about AWS IoT Core Setup for Venlite Energy Limited<\/strong><\/a>, which is an\u00a0energy and asset management company with a global audience footprint across and the Implantation of AWS IoT for Sharp Software,<\/strong><\/a> an innovative market-oriented engineering solution provider.\u00a0CloudThat<\/strong><\/a> offers cloud consulting services to our vast clientele to build IoT solutions and advance their businesses.<\/p>\n

Connect with our consulting architects for expert advisory<\/strong><\/a> to build innovative cloud and IoT solutions to suit your requirements and we will get back to you quickly.\u00a0Stay tuned for more on IoT, the cloud, and other emerging technologies in this space.<\/p>\n","protected":false},"author":259,"featured_media":9132,"parent":0,"comment_status":"open","ping_status":"open","template":"","blog_category":[4378,4046,3623,3606,3607,3832],"user_email":"vasanthr@cloudthat.com","published_by":"324","primary-authors":"","secondary-authors":"","acf":[],"_links":{"self":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/blog\/9130"}],"collection":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/blog"}],"about":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/types\/blog"}],"author":[{"embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/users\/259"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/comments?post=9130"}],"version-history":[{"count":2,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/blog\/9130\/revisions"}],"predecessor-version":[{"id":45682,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/blog\/9130\/revisions\/45682"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/"}],"wp:attachment":[{"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/media?parent=9130"}],"wp:term":[{"taxonomy":"blog_category","embeddable":true,"href":"https:\/\/www.cloudthat.com\/resources\/wp-json\/wp\/v2\/blog_category?post=9130"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}