Data optimises agricultural water use 
CategoriesSustainable News

Data optimises agricultural water use 

Spotted: As climate change makes weather and water supplies more unpredictable, it is vital that farming develops ways to use resources more efficiently. Data is playing an increasing role in this, by giving farmers better information on which to base decisions. One startup taking the lead on this is AguroTech. Founded in 2020, the company focuses on providing data and insights to farmers to help them use resources – such as water – more efficiently.

AguroTech has developed a platform that uses sensors, satellite and drone imagery, weather stations, crop and soil models, and more to provide unique and actionable recommendations to help farmers enhance their farm’s performance. The hardware and software provide farmers with real-time, artificial-intelligence-powered (AI) insights that can help them to better manage water, fertiliser, and pesticide use. The company will also soon be able to help farmers earn credits based on the amount of carbon stored in the soil.

The company is taking part in “LIFE – The Future of Farming”, an EU-sponsored initiative promoting collaboration between agricultural groups, farms, colleges, scientists, and municipal governments across Europe on mitigating damages caused by climate change.

AguroTech recently raised €1.5 million in a series A funding round led by VC Navus Ventures and ROM InWest. With this extra funding, AguroTech plans to scale further and expand internationally.

Improving farming yields while using fewer resources is the goal of a number of innovations Springwise has recently spotted. And it is a vital part of the response to global warming. These innovations include everything from a unique approach to regenerating desert lands to spreading rocks on farmland to capture carbon.

Written By: Lisa Magloff

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AI optimises supply chains and personalises retail offers
CategoriesSustainable News

AI optimises supply chains and personalises retail offers

Spotted: Recent years have witnessed two key retail trends: the move towards more personalised, curated customer offers, and pressure from stakeholders to tackle waste in the industry. UK-based Dressipi is working to tackle both issues with machine learning and artificial intelligence (AI). The company’s co-founders were inspired by their own first-hand experience struggling to find the products they wanted to buy.

Dressipi has developed a software platform that gives retailers the tools they need to personalise the shopping experience for individual customers. It does this by using a combination of human style expertise and AI to develop high quality product and brand data. Human stylists create a ‘taxonomy’ of fashion attributes that can be applied to each item. AI technologies, such as computer vision and natural language processing, are then used to apply these attributes at scale.

The same predictive models and algorithms that Dressipi uses to develop personalised insights can also be used to forecast buying and merchandising decisions. By better matching supply and demand, retailers can avoid waste in the supply chain, benefitting both their bottom line and the plant.

Dressipi’s technology has three key strengths. First, its algorithms have been developed over years in collaboration with human fashion experts. They are therefore specific to the needs of the fashion industry. Second, Dressipi owns extensive datasets of garment attributes and fashion-specific customer preferences, and the company’s ability to cleanse and parse all this data is the core of its offer. Finally, the company has a proven track record working with some of the industry’s leading names, delivering externally validated results.

Other AI-powered retail innovations spotted by Springwise
include personalised
wine recommendations, predictive
analysis to speed shipping, and computer
vision used for fashion cataloguing.

Written By: Matthew Hempstead

Website: dressipi.com

Contact: dressipi.com/company/contact/

Reference

A software service optimises decentralised energy projects
CategoriesSustainable News

A software service optimises decentralised energy projects

Spotted: The transition to a net-zero economy will require huge changes in our energy infrastructure. Not only will the power grids of the future be cleaner – they will also be more decentralised. In the fossil fuel era, energy infrastructure was owned by a small number of large players. But in the future, the fossil fuel supply chain will be replaced by much smaller assets embedded within the built environment. In the words of Australian startup Gridcognition, the energy transition represents a move away from ‘big dumb machines, to small smart ones’.

This transition represents a huge opportunity for the industry but comes with its own problems. One of the trickiest issues is the complexity of planning and assessing each de-centralised project – something that is beyond the scope of even the most sophisticated traditional spreadsheets. Industry players need to understand the environmental impacts and commercial opportunities of a diverse range of energy assets – such as virtual power plants, microgrids, community energy systems, and electric vehicle charging points. And they must also consider how each project interacts with the wider energy ecosystem and commercial landscape. Much more sophisticated data analysis is needed, and this is where Gridcognition’s software aims to play an important role.

The startup’s software service allows customers to simulate different energy project options based on a wide variety of different parameters – such as technical considerations, geographic location, and tariffs. The simulations crunch all this complex data allowing the user to quickly compare options based on commercial performance measures (such as cashflow) or environmental considerations (such as amount of CO2 emissions saved). The software also allows users to create a ‘digital twin’ of a project that can be updated as the project is deployed.

Gridcognition’s software is designed to be used by a range of different players including energy providers, project developers, solutions providers, large energy users, and property businesses. The startup has already secured a number of high-profile clients and partners, such as Amazon Web Services, and announced in October 2021 that it plans to expand into the UK microgrid market.

Other smart energy innovations spotted by Springwise include
a startup reducing
the impact of electric hot water systems, and devices that bring smart
meter technology to hard-to-reach homes.

Written By: Matthew Hempstead

Email: hello@gridcognition.com

Website: gridcognition.com

Reference