Latest / Internet of Things with Fexingo: Connected Devices, Sensors, and Industrial IoT / How IoT Sensors Are Digitizing Olive Oil Production
Transcript
- Lucas: So picture a hillside in Tuscany, maybe an hour outside Florence. Rows of olive trees that have been in the same family for four generations. And now, tucked under those trees, you've got soil moisture sensors every twenty meters, a weather station pinging data every five minutes, and a drone doing a thermal flyover once a week. This is olive oil production, wired end to end. Luna: Wait, olive oil? I feel like every IoT episode so far has been factories, warehouses, hospitals. Agriculture we've touched on with livestock and grain silos, but olive oil feels almost romantic. What drove this shift? Lucas: Two things. First, water. Olive trees are drought-tolerant but they still need precise irrigation to produce high-quality oil. In a region like Tuscany, where summer rainfall is becoming more erratic, farmers can't just guess anymore. Second, the quality premium. A bottle of extra-virgin that scores high on polyphenols and low on acidity can sell for thirty, forty euros. Sensors give growers the data to hit that sweet spot consistently. Luna: Right, so it's not just about saving water — it's about protecting the margin on a premium product. Do you have a specific case in mind? Lucas: Yeah, a fictionalized composite I'll call Frantoio Verde. Three hundred hectares near Montepulciano. The owner, let's call him Marco, inherited the grove from his father in 2018. He was skeptical of tech — his father used to say the trees know what they need. But after the 2022 drought cut his yield by nearly forty percent, he agreed to pilot an IoT system from a startup called TerraSense. Luna: What did the pilot look like? A few sensors, or the full suite? Lucas: Full suite on fifty hectares. They buried capacitive soil moisture sensors at two depths — thirty centimeters and sixty centimeters. Those measure volumetric water content. Above ground, they installed a weather station tracking temperature, humidity, wind speed, and solar radiation. And they did weekly drone flights with a multispectral camera that picks up canopy stress before the human eye can see it. Luna: That's a lot of data. How does Marco actually use it? Is he staring at a dashboard, or does the system tell him what to do? Lucas: Good question. The TerraSense platform runs an irrigation model that combines the soil data, weather forecast, and tree phenology — basically, what stage of growth the tree is in. It sends Marco a push notification: 'Irrigate block C tomorrow morning, forty minutes per dripper.' He doesn't have to interpret raw numbers. He just follows the recommendation. Luna: That sounds like the kind of thing that would win over a skeptical farmer. What were the results after the first season? Lucas: Over the 2024 harvest, the pilot block used thirty percent less water than the traditionally irrigated control block. But the bigger win was quality. The oil from the sensor-managed trees had a polyphenol count eighteen percent higher and acidity point three percent lower. That translates to a higher grade classification and roughly a twenty-five percent price premium at wholesale. Luna: So the ROI is pretty straightforward. How long until Marco recouped the sensor investment? Lucas: TerraSense charges about two hundred euros per hectare per year for the full service — sensors, drone flights, analytics. On fifty hectares, that's ten thousand euros annually. The yield increase and quality premium added roughly thirty-five thousand euros in revenue on that block. Payback was under one season. Marco expanded the system to his entire grove in 2025. Luna: That's impressive math. But I imagine not every crop has that kind of margin. Does this work for almonds or avocados too? Lucas: It does, but the payback period is longer. Almonds in California, for example — growers are using similar soil moisture and drone systems. The water savings are huge, especially during drought years, but the per-pound price of almonds is lower than premium olive oil. So you're looking at two to three seasons to break even. Still a solid investment if you're a large operation. Luna: Let's stay with olive oil for a moment. Irrigation is one thing, but the oil itself goes through fermentation and storage. Are there sensors in the processing phase too? Lucas: Absolutely, and this is where the tech gets really interesting. After harvest, olives are crushed and the paste is malaxed — slowly churned — to release the oil. Temperature and oxygen exposure during malaxation directly affect flavor and shelf life. Frantoio Verde installed IoT temperature probes and dissolved oxygen sensors in their malaxing tanks. The system alerts them if the paste drifts above twenty-seven degrees Celsius, which can degrade the oil. Luna: So it's not just field to table, it's field to bottle — every step monitored. What about storage? Olive oil is notoriously sensitive to light and heat. Lucas: Right. Their storage tanks have IoT temperature and humidity sensors, plus a light sensor that triggers an alert if a maintenance worker leaves a door open too long. They also installed a gas sensor that detects volatile organic compounds — if the oil starts to oxidize, the VOCs spike and they know before the flavor degrades. It's essentially predictive quality control. Luna: That's a level of precision I never associated with something as old as olive oil. Is the industry adopting this quickly, or is Marco an outlier? Lucas: It's still early, but adoption is accelerating. A recent survey by the International Olive Council found that about twelve percent of large producers in Italy and Spain have deployed some form of IoT. The biggest barrier is connectivity — many groves are in rural areas with spotty cellular coverage. TerraSense actually had to install a LoRaWAN gateway on Marco's property to relay sensor data, because there was no reliable cell signal. Luna: LoRaWAN — long-range wide-area network. That's the low-power, long-range protocol we talked about in episode three, right? Lucas: Exactly. It's perfect for agriculture because sensors can run on a coin-cell battery for years and transmit over several kilometers. Marco's gateway is solar-powered and mounted on the highest point of the property. It collects data from all the sensors and sends it to the cloud via satellite backhaul. No cell tower needed. Luna: So the infrastructure is actually getting cheaper and more self-contained. That's probably the biggest unlock for this type of IoT. Lucas: It is. And the next frontier is ai driven harvest timing. TerraSense is beta-testing a model that combines drone imagery, weather data, and historical yield records to predict the optimal harvest window for each block — not just by date, but by time of day. Picking in the cool morning versus the hot afternoon can affect oil chemistry. Luna: That's wild. So the algorithm is saying, 'Harvest block D on October 12th at 7 a.m.' — and the farmer just follows it. Lucas: Exactly. Marco told me that in 2025 he followed the AI recommendation for his early-harvest blocks and got the highest polyphenol score he'd ever measured. He said, and I quote, 'The algorithm knows my trees better than I do.' That's a pretty powerful endorsement from a guy who grew up trusting his gut. Luna: You know, this episode is exactly the kind of concrete, useful case study that makes me appreciate what we do on this show. If today's tech conversation gave you something usable — a new angle on precision agriculture, or even just a good story to tell at dinner — the way these stay ad-free is listener support. You can head to buy me a coffee dot com slash fexingo. No pressure, just keeping the lights on and the sensors beeping. Lucas: Yeah, I'll second that. We pour a lot of research into each episode, and knowing listeners find it valuable is what keeps us going. So if you're inclined, that's the link. Luna: Back to the grove. One thing I'm curious about — what happens to all this data after the harvest? Does Marco get a report, or is it streamed live year-round? Lucas: It's live year-round, which turns out to be useful for more than just irrigation. In the winter dormant season, soil moisture and temperature data helps Marco decide when to prune — pruning wet trees can spread disease. And the weather station tracks frost risk in early spring, when a late frost can kill the blossoms. Last April, the system sent an alert at 2 a.m. that temperatures were dropping below freezing. Marco was able to deploy frost fans in time and saved about sixty percent of his crop. Luna: So the same sensors that optimize irrigation in summer are protecting against frost in spring. That's a multi-use system that justifies the upfront cost even more. Lucas: Exactly. And the platform is adding more modules. This year, TerraSense launched a pest prediction model that uses temperature and humidity data to forecast olive fruit fly outbreaks. If the conditions are right, the system recommends applying a specific biocontrol agent — not a blanket spray, but targeted to the blocks at risk. Luna: That's the holy grail of precision ag — right input, right place, right time. And it's all built on the same IoT backbone. Lucas: It really is. And what I find exciting is that this isn't some sci-fi future. Marco's grove is a real example of IoT delivering measurable results today. The sensors are off-the-shelf, the connectivity is standard LoRaWAN, the analytics are cloud-based. Any producer with a few hundred hectares and a willingness to trust the data can replicate this. Luna: So as we wrap up, what's the one number you'd leave listeners with to sum up the impact? Lucas: I'd say thirty percent less water and eighteen percent higher quality in one season. Those two numbers capture why IoT is moving from factory floors into the fields. It's not about replacing tradition — it's about giving tradition better tools.