If you work in agrifood or environmental management, you inevitably need to decide where to allocate resources, when to act, and with which priorities.
And to do that, you need reliable, timely and readable data.
We are talking about concrete objectives: calculating carbon footprint, measuring water use and quality, assessing the biodiversity of soils and habitats.
This is not just sustainability reporting: it is about operations, business risk, reputation, and competitiveness.
Some global figures highlight the urgency of starting to measure fundamental environmental parameters rigorously and reliably.
Water-related figures are among the most pressing: over 70% of freshwater resources are used in agriculture. And with the world population expected to reach 9 billion by 2050, agricultural production is forecast to grow by +50% and water withdrawals by +15%.¹
Consequently, it is not enough to measure more, we need to measure better, with the right parameters, adequate frequency and a pipeline that turns raw data into operational decisions.
CLIMAVIBE turns environmental data into tools for better decision-making
The growing pressure on ecosystems and the lack of timely, reliable biodiversity data have made one thing clear: without integrated monitoring tools, it is impossible to make effective and prompt decisions.
It was from this awareness, the need to transform complex environmental data into actionable information for decision-makers, that CLIMAVIBE was born. A joint project between Tetis (a spin-off from the University of Genoa) and Wiseside, funded within the National Biodiversity Future Centre (NBFC).
The objective is simple to explain but complex to achieve: to monitor ecosystem biodiversity status with (almost) real-time data and translate them into clear indicators for those who need to act: companies, authorities, and managers.
In this context, biodiversity refers to the entire variety of life, from the genetic heritage of individual species to ecosystems as a whole, a dimension so broad and dynamic that it requires new and more precise tools to be monitored and understood².
Today, CLIMAVIBE does exactly this: it collects abiotic parameters (the physico-chemical conditions of water) and biotic ones (the biological signals of the habitat), ensuring continuity and traceability of measurements over time. It also synthesises the information into readable indices and issues alerts when persistent critical issues arise.
A lagoon as a testbed for biodiversity measurement
The experimentation takes place in a lagoon ecosystem: shallow, dynamic waters, sensitive to salinity and nutrients, and rich in ecosystem services, i.e. the benefits natural ecosystems provide to humans, from climate regulation and water purification to biodiversity protection.
These are representative, yet also strategic, environments in which to test a continuous and reliable measurement system.
We have installed sensor hubs at three different points of the lagoon to collect: temperature, salinity, dissolved oxygen, pH, turbidity.
Additionally, an underwater camera has been installed to monitor fish fauna.
Measurements are taken frequently (≈ every 20 minutes) and sent to iChain, our analysis platform for data processing and visualisation.
The role of the platform: iChain as the backbone
What holds everything together is iChain, the Wiseside platform that manages data in an integrated, continuous way across the entire chain, transforming it from raw information into an operational tool for decision-making and action:
- Automatic collection from sensors and field sources,
- Normalisation to make different data series comparable,
- Structured, historicised storage,
- Dashboards and KPIs for fast and efficient interpretation,
- Traffic light–based alerts to signal where action is needed.
Thanks to iChain, heterogeneous data flows become actionable information for technicians and decision-makers, with audit-proof traceability and historical records.
This delivers two immediate advantages:
- Continuity: data are accumulated systematically, increasing their value over time.
- Comparability: different parameters, stations, and periods are placed on the same level, enabling the identification of patterns and anomalies with greater confidence, even in the long term.
From monitoring to decision-making: a single indicator that simplifies everything
To make complexity readable, CLIMAVIBE uses a synthetic Lagoon Biodiversity Index (LBI) with a 0–1 scale and colour-coded quality classes (green/yellow/red/black).
It may sound complex, because there is extensive scientific research behind it, but the mechanism is intuitive: each environmental parameter measured receives a score. These scores are then summed and reprocessed to create the overall index.
Finally, a traffic-light system translates the result into an immediate signal. This way, a single indicator provides an at-a-glance view of the ecosystem’s condition.
If a critical issue persists for a certain period, the platform generates an alert: not an academic judgement, but an operational signal to decide what to do and when.
Beyond the lagoon: CLIMAVIBE as a replicable model for companies and territories
CLIMAVIBE is not an isolated case, it is a method.
The combination of sensors + structured collection + iChain + indicators can be replicated in many contexts:
- Agricultural areas (irrigation management, soil quality, crop biodiversity),
- Water basins and protected coastal/marine areas,
- Carbon projects with co-benefits that need to be demonstrated, not just declared.
In short, the same pipeline works wherever accurate measurement and timely decision-making are needed: from agricultural districts to agrifood supply chains wishing to integrate credible environmental indicators into their KPIs.
What changes for managers?
- Time: we move from “spot” campaigns to continuous historical series revealing seasonal patterns and trends.
- Quality: data are harmonised and made comparable, so indices are robust and shareable.
- Action: alerts support targeted interventions, justify decisions, and facilitate dialogue with stakeholders and the supply chain.
Do you want to find out which technologies and tools made all this possible?
In the next article, we will delve into the practical side: the parameters we are measuring, the technologies used, and the role of iChain, from sensors to KPIs.
In the meantime, if you want to understand how to set up useful data collection in your supply chain, get in touch: we can guide you through a 30-day iChain-based journey, with ready-made KPIs and alerts to deliver immediate, measurable results.
References
- Groundwater Quality Assessment and Irrigation Water Quality Index Prediction Using Machine Learning Algorithms, Enas E. Hussein et al., 2024
- Purvis and Hector, 2000
CEO of Wiseside Srl, thanks to his solid experience in the IT sector and consulting for multinational companies, she has been contributing for over 10 years to the development of innovative and collaborative Supply Chain models, always respecting the principles of sustainability.
