Notice: Undefined index: HTTP_REFERER in /var/www/html/wp-content/plugins/wp-cors/wp-cors.php on line 28 Notice: Undefined index: HTTP_ORIGIN in /var/www/html/wp-content/plugins/wp-cors/wp-cors.php on line 29 Agriculture using IoT - Pycom Internet of Things Customer Stories

Land for farming is decreasing. We’re worried about clean usable water resources and we need to stop polluting the planet. This means that farmers have to be smart about both crop and livestock management to lower pollution, waste and all of this while maintaining profitability by continuing to reduce costs of farming in general. Not an easy job!

Enter data-driven tactics and connected technologies under the banner of IoT

It is regularly stated that IoT has a wide variety of applications. The Internet of Things crops up repeatedly for use cases in industrial manufacturing, utilities and asset tracking. So, it should come as no surprise that it also is highly applicable to farming.

If you are a regular reader of Potato News Today, you may have seen their recent article on the rising popularity and increasing number of use cases of IoT being used by farmers. Although the term agri-tech generally refers to any way in which technology is applied to agriculture, it is becoming more and more commonly used to refer to deployments of IoT sensors, drones and even AI. In a world that has an ever-growing number of mouths to feed, technology will be relied upon even more heavily to make farming as efficient as possible. After all, it’s not going to be easy to feed 9.7 billion mouths by 2050.  

Farmers have always had a huge number of things to monitor and measure; from soil moisture to fertiliser levels to livestock monitoring. In the past, farmers made field-by-field assessments which is very time consuming and tedious. This is where IoT comes in, as it can help remotely manage and monitor what was previously done manually. 

Sometimes this is referred to as IoT-based smart farming (a bit of a mouthful), which is when a system is built that utilises IoT sensors for things like light, humidity, temperature and soil moisture and then can combine that with an automated system. According to’s report the global smart agriculture market will reach approximately $9.3 billion – which is not a sum to sniff at!  

Why is precision farming so darn important?

The Financial Times picked out precision farming as one of the ways that we can change an industry that is often labelled as highly damaging to the environment. The environmentally friendly change comes about through data monitoring, which directly influences how a farmer utilises his resources i.e. precise practices can be introduced and therefore output is optimised, and less waste occurs.

To give an example of this, the E.J.Gallo Winery in California teamed up with IBM’s Watson, and by monitoring when and where the grapes needed to be watered, it reduced the water usage by 25%. However, the FT points out that often internet connectivity can prove a problem in developing countries, which is when LPWANs might be able to step in. Of course, this is use-case dependent but nevertheless, the more networks there are then the higher the likelihood of successful coverage.  

The UK government has selected Precision Farming as a massive area for exploration, as it has drawn down £5 million from the Industrial Strategy Challenge Fund to invest in UK and Chinese businesses that are developing precision farming technology. Farmers in the UK already have to use accurate land and activity data when entering into environmental schemes or making subsidy claims, and accurate monitoring will only become more important as time progresses.  


What is the difference between precision farming and smart farming?

McKinsey & Company define precision agriculture as a “technology-enabled approach to farming management that observes, measures and analyses the needs of individual fields and crops”. This is then shaped through two different trends: ‘big-data and advanced-analytics capabilities…and robotics”. By robotics, McKinsey lists things like aerial imagery, sensors and sophisticated local weather forecasts.  

However, this differs slightly from the European Parliament’s definition of precision agriculture as “a modern farming management concept using digital techniques to monitor and optimise agricultural production processes”. Precision agriculture is all about optimisation for the European Parliament; they use the example of optimised fertiliser usage where fields are measured, and within-filed soil variations are monitored.  

Either way, both parties agree that precision agriculture is the targeted application of agricultural inputs, such as water and fertiliser, to achieve a desired harvest.  

Smart farming is slightly different, as it is the title applied to the application of information and data technologies for optimising complex farming systems. The focus is on the access to data and the application of the data I.e. how the data collected can be used in a smart way. It involves all farm operations, not just individual machines.  


Livestock monitoring as part of agri-tech

Without wanting to, most farmers lose some animals every year. They get ill, die of undetected causes, go AWOL, grow too fast, not fast enough or not at all. Farmers then lose revenue and profits. This is to some extent avoidable and that is why farm operations increasingly  look for clever ways of getting smart livestock management solutions put in place. There are quite a few of those available today and many more being developed. These include livestock wearables with sensors that monitor health, growth, location and other vital information. We’ve also seen some clever solutions the deliver automatic weight management and smart herd tracking. There will be more, we’re sure.


Why is IoT good for agriculture?

IoT is perfect for agriculture for a number of different reasons. It allows real-time data collection and can monitor a huge range of things that affect farming. There are a variety of different sensors available; pH sensors to monitor acidity, temperature and humidity sensors that apply perfectly to a greenhouse application and GPS tracking for monitoring livestock.  

One of the main draws is that LPWANs allow farmers, or providers, to set up their own LoRa-based mesh network. LoRa is a fantastic LPWAN for autonomous work and monitoring, as the set-up process is very low-touch.  

Another reason that IoT is being widely rolled out for agriculture is the fact that the hardware is very low-cost. Most devices are not very expensive and the return on investment can be huge! (Also, keep your eyes peeled to our social media feeds as we are currently in the process of bring out a sensor range as we want to make your Proof of Concepts as flexible as possible.)  


Next, you might be wondering how our boards are used in agriculture…

Roll in one of our customers, Northstar Systems, a Canadian Agriculture solutions provider.

Any board that is deployed remotely has to be hardwearing, as they are exposed to a huge temperature range as well as a number of other factors such as dust, dirt and differing power sources. Luckily, our boards are (within reason) very hardy. North Star Systems Inc are a Canadian agricultural company that are ‘focused on real-time controlled remote monitoring for various liquid and pressure vessel tanks.’  They chose to use Pycom products as they were easy to get started with and required very little hands-on time. North Star didn’t have to reinvent the wheel, as we were able to give them the technology they wanted very quickly. 

They are currently using Pycom’s LoPy4 and WiPy boards as two of the core CPUs that control all aspects of some of their embedded systems and boards. This is vital to maintaining remote operations and for their users to receive data regarding things such as the temperature and liquid level within their tank, using pressure and float sensors.  The LoPy4 is capable of WiFi, BLE, LoRa, and Sigfox communications. 

One of the key decision-making factors was that Pycom’s boards offered multi-network connectivity. Rural areas infamously suffer from very poor network coverage so having a variety of different LPWANs available means that if one network doesn’t cover a particular area, then another one might.