In the sun-scorched expanse of North Horr, a remote corner of Kenya located 727 kilometres north of Nairobi, where temperatures routinely soar past 40 degrees Celsius and the land cracks under an unforgiving sun, a quiet revolution is taking shape.
At Tiigo Primary School in Marsabit County, artificial intelligence is silently offering farmers, herders, and teachers a lifeline against the unpredictable forces of climate change.
Rising above the school’s dusty playground stands a sleek, solar-powered weather mast. To the casual eye, it may appear unremarkable. Yet this simple structure houses a transformative AI-powered hyperlocal weather forecasting system, a lifeline in a region where unpredictable weather means the difference between life and death.
“We used to send children home early—either from unbearable heat or sudden storms,” recalls David Denge, the school’s principal. “Now we have foresight. We can plan lessons. We can protect lives.”
The weather station is the product of a partnership between Wireless Planet Limited, Juhudi Mashinani, Aenki e.V., and the North Horr Constituency.
Equipped with advanced sensors tracking temperature, humidity, wind speed, UV index, rainfall, and barometric pressure, it leverages LoRaWAN — a low-power, wide-area wireless technology that works without SIM cards or mobile data — making it perfectly suited for remote, off-grid environments like North Horr.
For students, the weather mast is an open-air science lab; for teachers, it is a dynamic, real-time educational tool; and for the pastoralist communities who surround the school, it is an indispensable resource amid accelerating climate uncertainty.
Traditional weather forecasting in this community, passed down through observation of clouds, animal behavior, and oral legends, has been increasingly unreliable in the face of erratic climate patterns. Into this void comes data-driven insight.
“This is AI that understands the land,” says Leonard Mabele, founder of Wireless Planet. “Unlike top-down models built in Nairobi or abroad, this system learns from real-time data collected at the village level. That’s the real breakthrough.”
Through machine learning, the system builds precise, predictive models honed to very specific localities.
Critically, these AI forecasts are supplemented by datasets from the Kenya Meteorological Department (KMD) and the Kenya Agricultural and Livestock Research Organization (KALRO), delivering precision tailored not just for schools but also for farmers and herders grappling daily with climate volatility.
Predictive agriculture and localized climate adaptation are no longer distant ideals but practical, community-owned solutions changing lives in one of Kenya’s most vulnerable regions.
At the heart of this project is local ownership. “We’ve seen too many projects come in with good intentions but no sustainability,” reflects Abudo Katelo, Chairperson of the Turbi Ward Climate Committee. “This one is different. Our youth are being trained. Our elders are being involved. Our schools are becoming community hubs.”
Geography lessons now weave in real-time weather graphs, creating a vibrant dialogue between schoolchildren and elders that bridges generations. Local elders like Mzee Issacko Dida have embraced this technology, not as a replacement of ancestral knowledge, but as a powerful complement. “We watched the sky, the goats, the winds,” he says. “Now we also watch the data. We are combining knowledge. That is power.”
Spurred by the success of the North Horr pilot, the initiative is scaling rapidly. In Busia County, located 465 kilometres west of Nairobi, 25 schools, including St. Mary’s Butula Girls and St. Paul’s Namahindi Secondary, have adopted the system to provide AI-powered advisories to smallholder farmers.
Weather data flows seamlessly into a centralized cloud platform, where it is analyzed for insights and then relayed back to farmers via SMS and mobile apps.
Concurrently, agricultural extension officers receive training to interpret this data and translate it into practical advice on irrigation scheduling, planting calendars, and livestock management. “We’re not just giving people data,” Mabele emphasizes. “We’re giving them the confidence to make better decisions. We’re building digital citizenship in places long left off the grid.”
In Kenya, where over 5 million smallholder farmers produce nearly 75 percent of national food yet remain highly vulnerable to climate shocks, such precision forecasting isn’t a luxury; it’s essential.
Beyond climate adaptation, the initiative is nurturing a generational shift. At Tiigo and beyond, students learn to analyze data, program sensors, and comprehend complex climate systems.
Girls, traditionally underrepresented in STEM fields, are taking active roles in coding and analytics clubs. “We’re not just building tools,” says Mabele. “We’re cultivating talent. These students won’t just consume AI, they’ll create it.”
The integration of AI into local resilience planning is gaining applause among practitioners and researchers alike. Marsabit environmental scientist Somo Guyo and computer scientist Hassan Jattani have developed JangaVoice, a disaster risk reduction platform enabling communities to report early warning signs of drought, disease outbreaks, and floods through accessible mobile apps and USSD interfaces.
“We need unified, AI-enabled models that empower citizens to participate in preparedness and response,” Guyo explains. “Integration of tools like JangaVoice with weather systems could personalize disaster response and ensure local ownership.”
Ajira Digital’s regional trainer, Onesmus Mworia, urges the creation of scalable, inclusive systems blending local and global climate datasets so that farmers in even the most isolated regions are not left behind.
Meanwhile, Collison Lore, formerly of IGAD’s Climate Prediction and Application Centre, calls for a common language in climate data collection and greater interoperability among national and community-based systems. “AI isn’t just a tool,” he insists. “It’s an opportunity to bring communities, governments, and technologists into a shared, accountable conversation.”
At the recent AI for Sustainable Food and Agriculture virtual summit, hosted by the IEEE Technology Climate Center (ITCC) and CEIMIA, experts underscored the stakes of democratizing AI development worldwide.
Dr. Thomas Mboa, CEIMIA’s researcher-in-residence, stressed African leadership in global AI policy, emphasizing that technology must be shaped to serve local needs and foster meaningful development. “Africa must not be a passive recipient,” he declared. “It must shape how AI serves its future.”
Digital innovation architect Erik Van Ingen echoed this imperative, highlighting AI’s potential to reduce food waste, track fish stocks, and synchronize supply chains across Africa’s agrifood systems.
As Mabele puts it, “It may look like just a pole,” gesturing to the weather mast tall above Tiigo’s playground, “but to us, it’s a bridge to a future where we don’t just endure climate change. We respond. We adapt. We lead.”
Here, in one of the world’s most remote and climate-vulnerable places, intelligent choices powered by technology and grounded in community are forging a new path, one where resilience is reimagined, and hope finds its roots in the collaboration between ancient wisdom and cutting-edge AI.
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