Managing warehouses with machine learning
CategoriesSustainable News

Managing warehouses with machine learning

Spotted: Although many people returned to in-person shopping after the COVID-19 pandemic, e-commerce has continued to grow and is expected to make up nearly 20 per cent of all retail sales in 2023. At the same time, the need for efficient logistics is growing, with the market for warehouse management systems poised to reach $12.3 billion (around €11.2 billion) by 2031. 

One new player in this field is Fulfilld, which has developed an innovative platform that uses real-time data to optimise warehouse operations by coordinating tasks between humans and robots. Fulfilld’s platform harnesses cloud-based technology, ultra-wideband connectivity, RTLS beacons, scanners, tags, and digital-twin warehouse simulations to connect systems and track real-time flow. 

The system includes both software and hardware, in the form of hand-held scanners with natural language processing capabilities, to optimise inventory and co-ordinate task instructions to both human and robotic workers. The startup’s artificial intelligence (AI) and machine learning models can also proactively recommend “on-the-fly opportunities” for better warehouse optimisation. 

The system further co-ordinates tasks and inventory locations and creates a Google Maps-like solution for warehouse workers. 

Fulfilld aims to serve mid-market customers in industries including warehousing, manufacturing, distribution, and logistics. It offers a subscription package that allows for rapid roll-out. The novel technology, the startup claims, can boost efficiency by 15-20 per cent, and reduce employee turnover – a crucial benefit amid labour shortages and supply chain disruptions. 

Many companies are calling on robots to help optimise operations across various sectors, including to build houses and support security guards.

Written By: Lisa Magloff

Reference

AI and remote sensing technology for managing water risk
CategoriesSustainable News

AI and remote sensing technology for managing water risk

Spotted: By 2030, the world’s communal demand for fresh water is expected to outstrip supply by 40 per cent. How to avert this crisis is a question many innovators, researchers, and agencies are working to answer. And sustainable management of the water that is currently available is a crucial aspect of the global solution. 

Understanding the health of the world’s bodies of water, along with current and potential future risks is vital, and San Francisco-based technology company Waterplan has created a platform that uses remote sensing and artificial intelligence (AI) to track, analyse, and mitigate the risk to global water supplies.  

The platform helps organisations of any kind plan for the future by protecting water supplies now. The highly detailed reports include data from regulatory reviews, watershed authorities, industry analysis, scientific research, and more, with information presented in easily navigable formats. Clients view data by site and can see at a glance which areas need risk mitigation first.  

The reports are structured in a way that makes them usable for investors, and client input helps shape what areas the AI tracks. Sustainability managers use the platform to track progress against targets and measure the efficacy of various interventions. Operations managers can use the platform to maintain peak productivity across all processes and locations, as well as predict adjustments needed based on changing conditions.  

With the need for robust data continual, Waterplan recently closed an oversubscribed series A financing round that raised $11 million (around €10 million).  

Cleaning polluted water is one way to improve the quantity of supply, and examples from Springwise’s archive include a membrane that generates electricity while cleaning wastewater and a modular sewage treatment plant that fits inside a shipping container.

Written By: Keely Khoury

Reference