Precision farming is on the rise. The process involves the constant monitoring of the state of crops in order to provide the perfect growing conditions. It is being used to improve productivity and the sustainability of farms but has traditionally been expensive to implement. As a result, current applications are unlikely to see widespread use – particularly considering 78% of the world’s produce is grown in developing countries according to the Brookings Institute.

Despite high demand for farmed produce, many of those employed in agriculture in much of the developing world are still relatively poor. Just 12% of their crops are high value ‘cash crops’ suitable for export. Implementing new technology driven farming techniques is therefore restricted to a small section of the agriculture industry. The World Bank identifies agricultural development as a key means of poverty reduction. Technology if affordable, would, therefore, make a particularly positive impact.

In Africa, we’ve already seen the emergence of farming apps such as EZ Farm which uses predictive analytics to advise farmers on useful things such as moisture levels in the soil. However, by inputting real sensor is driven data on weather, soil types, the slope of the land, moisture, heat, chemicals and other conditions; water, fertiliser and pesticides could be applied in more precise quantities specific to crops needs to increase productivity.

Groundbreaking firms such as Arable are already leading sensor innovation, developing new means to provide insights into crop health. The core of the cost and challenge, however, comes most often in the transmission. Farming by nature is conducted over enormous areas of land, typically with little access to mobile data. Those early adopters have therefore often been forced to set up their networks across considerable areas of land – at a very high setup cost. As a result, to date, those without available investment have been unable to benefit from a connected farming environment.

In the areas where networks exist, costs can still be particularly high, and issues around connectivity and signal strength will persist. The hype around Industrial Internet of Things solutions from mobile network operators running on 4G (and later 5G) mobile networks has encouraged some level of uptake. However, these systems are limited in their capabilities in that they are reliant on network efficiencies and costs can also be very high. We’ve all been without a data connection when we should, or in areas where traffic is too high to connect. Service issues are almost accepted in the consumer market, but in an industry as essential as agriculture, existing network reliability simply isn’t sustainable to run monitoring equipment on. Furthermore, the cost of running a connected SIM which supports LTE often far exceeds the value of the data. Also, the processing power required to transmit the data is high and can take up unnecessary amounts of space.

It is clear that a more efficient and affordable means to introduce remote monitoring into farming could make a clear difference to farmers globally. In my view, the ideal technology is a relatively little-known one – Unstructured Supplementary Service Data (USSD).

[easy-tweet tweet=”USSD requires far less signal strength than mobile data meaning less power demand.” hashtags=”Data, Agriculture”]

Effectively the internet without the internet and a feature within all cellular networks 2G to LTE, USSD provides a means to transmit information in regions where there is little to no mobile data coverage available. Implemented correctly into the agriculture industry, it could provide some immediate cost savings and enable remote monitoring at an affordable price point for more farmers.

USSD requires far less signal strength than mobile data meaning less power demand, allowing devices to last longer in the field. For agriculture, this makes sensors simple to install in and around crops. There is no need for microprocessors and components to communicate the data – in turn reducing costs for manufacturing.

USSD does depend on GSM networks, however with only 20% of the globe’s population without access to basic mobile services, according to the GSMA, and with this number continuing to shrink, USSD could help to drive adoption of more automated farming in multiple regions.

Making available more efficient and affordable technology to improve agriculture processes would provide the essential catalyst to unlocking farming inefficiencies globally. There is a lot of hype around agri-tech, despite how clever the predictive analytics application is in the cloud – the data needs to come from the field. Given most fields are in low data coverage areas but are almost always in far-reaching GSM reach, USSD seems like the perfect partner to advancement.

The technology is available now and does not require support from mobile networks or governments to implement. The ball is in the court of the agriculture industry; time will tell how they chose to utilise these available solutions.