e-kakashi

SERVICE

Environmental data and work information together as onee-kakashi and Gateway

The basic "e-kakashi" set. Measure the environment by installing various sensors on the field.

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CASE STUDY

2018.03.14

Smart and Sustainable Agriculture with IoT

#Institute #Open field #Rice

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NEWS

2025.06.03

Selected as a Grant Recipient for the Ministry of Agriculture, Forestry and Fisheries of Japan's "Emergency Support Project for Agricultural Recovery in Ukraine"

# Pressrelease #Greenhouse #tomato #Cucumber

2025.04.16

Double adoption by the Ministry of Economy, Trade and Industry (METI) for the Global South Future-oriented Co-creation Project

# Pressrelease #environmental conservation #soybean #sesame #corn

2025.04.04

Participation Report: Japan-Brazil Economic Forum

#News #Event

2025.04.03

Supporting Agricultural Recovery in Ukraine Feasibility Study Initiated

#News

2020.12.04

Introduced in "The Japan Journal"-Digital Transformation for Development: Japan's Contribution-

#Institute #Open field #Rice

2020.08.24

A keynote speech at AgroFuturo 2020

#Institute #Open field #Event #Rice #Agricultural Association #Farmer

2019.10.28

SoftBank Corp.’s AI-powered ‘e-kakashi’ Solution for Sustainable Agriculture Adopted for Smart Rice Farming Project in Colombia

#Institute #Open field #Rice # Pressrelease

2019.10.25

e-kakashi introduced on "The Japan Agri News"

#News #Greenhouse #strawberry #Agricultural Association #Farmer #Local Government

2018.05.22

Webinar Organized by the US Journal “Science” Sponsored by a Japanese Company for the First Time

#News #Institute #Event

2018.04.19

Platinum Sponsor e-kakashi Supports “Science Robotics Meeting in Japan” held by the American journal Science

#News #Event

"e-kakashi" in South America

VISION

Greein Inc.
Representative Director and CEOTakashi Togami Ph.D.

Not a technical point of view, think what you have to do from the plant perspectives

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Greein Inc. Director CTOKyosuke Yamamoto Ph.D.

e-kakashi's hybrid AI applies plant physiology, and enables meaningful predictions with limited volume of data