Dr Juliet Obaro, Internet of Things(IoT) engineer, says that Edge Artificial intelligence (AI) can bridge connectivity gaps and capable of empowering smallholder farmers with real time agricultural insights.
She said this in an interview with the News Agency of Nigeria (NAN), on Thursday in Abuja..
Obaro explained that Edge AI was an emerging technology that allows data processing to occur directly on devices without reliance on continuous internet connectivity, therefore can revolutionise farming practices in underserved communities.
She said the biggest barrier to digital agriculture was not the lack of innovation but the dependence of most solutions on internet access which remains unreliable in rural farming clusters.
“Most smart farming tools today are cloud-dependent, meaning they require constant internet connectivity to function effectively.
“But for rural farmers, especially those in remote communities, this model simply does not work,” she said.
She said Edge AI addressed this gap by embedding intelligence directly into farm-based devices such as sensors, drones, and handheld tools, enabling them to analyse data locally, providing immediate feedback to farmers.
Obaro told NAN that with Edge, devices could process soil conditions, weather patterns, and crop health data on the field without sending that data to distant servers.
According to her, this means farmers get real-time insights even when they are completely offline.
She explained that such systems could be deployed through low-power IoT devices equipped with pre-trained machine learning models capable of detecting crop diseases, monitoring moisture levels, and predicting yield outcomes.
“Imagine a smallholder farmer in a remote village being alerted instantly that his crops are under pest attack, or that soil moisture is critically low without needing internet access.
‘That is the power of Edge AI,” she told NAN.
Obaro further highlighted that the integration of solar-powered devices could enhance the sustainability of Edge AI systems in rural areas where electricity supply is also a challenge.
She identified power as another constraint adding that designing these systems to run on solar energy would ensures that farmers were not limited by grid electricity.
According to her, this makes the solution adaptable to rural realities.
She said localisation of AI models was crucial for effectiveness, noting that procedures should be tailored using data specific to Nigeria’s climate, soil types, and crop varieties.
“AI systems built with foreign datasets may not perform well here.
“We need locally trained models that understand indigenous crops like cassava, yam, and maize, as well as region-specific pests and diseases,” she said.
She further told NAN that Edge AI reduces operational costs for farmers by eliminating the need for expensive data subscription and cloud storage services.
Obaro said that for smallholder farmers who operate on thin margins, affordability is imperative.
She maintained that Edge AI significantly lowers recurring costs because once the device is deployed, it can function independently.
On data security, Obaro explained that Edge AI offered an added advantage by minimising data transmission risks.
She said since most of the data processing happen locally, there would be less exposure to cyber threats associated with cloud-based systems, with farmers retaining more control over their data.
In spite of its potential, she acknowledged that challenges such as initial deployment costs and limited technical expertise remained.
“Like any emerging technology, there are barriers, but with the right policies and incentives, these can be overcome,” she said.
She expressed optimism that the AI could play a transformative role in achieving food security in Nigeria.
