CASE STUDIES

The urgent challenge of ensuring a sustainable water supply is exacerbated by climate change, with aging infrastructure, budget constraints, and a shortage of skilled workers hindering water pipe network maintenance.

Tenchijin addresses this by utilizing smart data from satellites, land, water pipe networks, and maintenance records, feeding it to AI to create precise risk maps for water leaks.

This solution aids water utilities in minimizing non-revenue water, optimizing operations, and reducing costs amid a limited workforce, ensuring accuracy and trustworthiness.

Tenchijin's KnoWaterleak system addresses water pipe leaks from internal factors like reduced thickness and pressure shocks, and external factors like temperatures and land motions.

By integrating earth observation satellite data with water utility information and using machine learning algorithms, it assesses leakage risks in 100m square areas, enhancing efficient confirmation and management.

On average, KnoWaterleak helps water suppliers: walk 20 times less ground to find leak, find 20 times more leaks, reduce cost to find leak by 10, save 50% of their budget

Currently 4 municipalities in Japan use the solution. It is expanding to entire Japan, Europe and other Asian countries.

Since the Paris Accords (COP 21, December 2016), hundreds of countries have pledged to slash greenhouse gases emissions from fossil fuels by 50% by 2050.

To accompany the increasing energy demand and keep Earth livable, renewable energy capacity should exceed 5000 GW., which would translate in enormous clean revenues.

Consequently, the competition to find the best land is fierce and it warranted to accelerate the provision of permits.

Traditionally, contractors have used their intuition and experience to find suitable wind farm sites based on map information and wind information, and have gone to the site to erect poles and take measurements.

Tenchijin was able to find suitable sites for wind power generation by calculating the efficiency of wind power generation from more detailed wind data and satellite data on topography and precipitation.

Development of a dedicated compass for energy companies
We aim to develop our business by working not only on wind power, but also on solar power.

Carbon offsetting means reducing emitted carbon dioxide (CO2) by an equivalent amount elsewhere. emissions, thereby reducing the amount of CO2 emitted. Carbon offsetting is one way of reducing greenhouse gas emissions.

For example, suppose a company emits CO2 at its factory. The company can cover the amount of CO2 emitted by its factory by reducing an equivalent amount of CO2 elsewhere. This is called carbon offsetting.

In the global effort to reduce methane emissions, Tenchijin has innovatively developed a patent-pending methodology for estimating methane emissions from paddy fields.

This unique approach leverages Tenchijin's expertise in satellite data, AI analysis, and paddy field agriculture.

It excels in utilizing optical and SAR satellite imagery along with climate data to comprehend the "history of water management," a crucial factor in methane emissions.

The TCFD Task Force mandates national disclosure of companies' carbon emissions.

This prompts businesses to assess their entire supply chain, challenging them to include climate impact information in ESG investment assessments.

To attract ESG investments, companies must act on climate change.

Tenchijin's project aims to measure carbon in paddy fields, forests, and livestock farming, developing carbon credits through accurate carbon measurement to support companies in meeting these disclosure requirements.