This landscape identifies 101 patent families published between 2015 and mid-2026 that combine smart, precision or irrigation-control language with water-use efficiency or loss-reduction claim text, filtered to relevant irrigation and climate-adaptation IPC classes. That is a bounded search set, not a count of every irrigation patent worldwide, so broader or narrower search terms will return different totals. The most recent year's count will also rise as publications with an 18-month filing lag continue to appear.

Filing activity in this dataset is led by academic and engineering institutions rather than a single dominant corporation, with the strongest historical corporate presence coming from an established irrigation-control filer whose family line anchors the citation rankings. Recent-year momentum, however, sits mostly with colleges and universities filing small numbers of applications rather than sustained corporate programmes. Anyone tracking competitive activity here should watch institutional filers alongside corporate ones, not instead of them.

India and China are the dominant receiving offices in this corpus, together accounting for roughly 78% of the 101 records, with the United States a distant third. Australia, the European Patent Office and the Netherlands each contribute only a handful of filings. A freedom-to-operate review limited to US or European jurisdictions would miss most of the activity captured here.

Start with the volumetric budget-based irrigation control family, which carries the highest citation counts in this corpus and appears across multiple related US and international filings. A third of all records in this landscape also classify under control-and-regulation systems, so scheduling and control-logic claims are the most crowded area. Checking that family line and its citing patents before drafting new control claims will reduce the risk of overlap.

Yes, based on the IPC composition data: subclasses covering soil-working integration, material-analysis-based water-loss diagnostics, and non-electric control variables each show single-digit record counts compared with over a hundred in the core horticultural class. Combined with the small but growing overlap into AI-based scheduling models, these lower-density branches suggest room for claims that link irrigation control to specific sensing or planting-system integration rather than general scheduling logic. High filing density in the core control class means that area is occupied, not that it is closed to well-differentiated claims.