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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 soil . However , by inputting real sensor driven data on weather ,

soil types , 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 own 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 . 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 . In addition , 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 ).

Effectively an 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 a number of 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 literally 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 .