A look at the current state of IoT in monitoring biodiversity loss and climate change, with examples of how it is being used to monitor vulnerable ecosystems
Charles McLellan / TechRepublic : Tweets: @vodafoneiot , @techrepublic , @techrepublic , @techrepublic , and @techrepublic . Thanks: @steveranger Tweets: Vodafone IoT / @vodafoneiot : .@TechRepublic explains how #IoT could be used to fight #ClimateChange & loss of biodiversity on our planet: https://www.techrepublic.com/ ... @techrepublic : The potential to install benign surveillance over the natural world is immense, ranging from earth-observation satellites to smartphones listening for chain saws in the forest. Read https://www.techrepublic.com/ ... by @charlesmclellan #longreads #climatechange #biodiversity #IoT #AI https://twitter.com/... @techrepublic : Snapshot Serengeti has been classifying images of animals captured by a grid of camera traps in Tanzania's Serengeti National Park since 2010. Learn more in this #longread (free PDF): https://www.techrepublic.com/ ... by @charlesmclellan #AI #IoT #climatechange #conservation https://twitter.com/... @techrepublic : @OfficialZSL uses Instant Detect, a monitoring system that combines sensors, cameras, radio networks, and satellite tech to capture and transmit real-time information on wildlife and human activity anywhere in the world. Learn more in this #longread: https://www.techrepublic.com/ ... https://twitter.com/... @techrepublic : If tropical deforestation were a country, it would rank third behind China and the US in CO2 emissions. Read The Internet of Wild Things: Technology and the battle against #biodiversity loss and #climatechange https://www.techrepublic.com/ ... by @charlesmclellan #longreads #IoT #AI https://twitter.com/... Thanks: @steveranger
Context & Ripple Effects
TechRepublic's longread by Charles McLellan frames what earlier coverage showed in pieces: a nonprofit's treetop unit that uses AI and repurposed cellphones to detect chainsaws against illegal logging, and Snapshot Serengeti's camera-trap grid classifying animal images in Tanzania since 2010. The through-line is that conservation sensing has moved from one-off projects toward layered systems — ZSL's Instant Detect already combines sensors, cameras, radio networks, and satellite links to transmit real-time wildlife and human activity data.
What makes the survey timely is that the building blocks are getting cheaper and more contested at once: conservationists are now shipping open-source tools like a $150 Field Kit sensor hub, while public species-mapping databases have had to rebuild their infrastructure to hide endangered-species locations from poachers.
First-order effects
- Conservation operators such as ZSL and the Snapshot Serengeti project gain real-time visibility into both animal activity and human incursions, shifting patrols and research from retrospective sampling to live response.
- Connectivity players like Vodafone IoT get a concrete vertical: remote ecosystems need wide-area networks, making biodiversity monitoring a commercial use case for carrier-grade IoT.
Second-order effects
- As sensing spreads, adversaries adapt on both fronts — logging operations face acoustic detection in the canopy, while the same public databases that aggregate sightings must keep obscuring exact locations of endangered species from poachers.
- Falling hardware costs, exemplified by the $150 Field Kit approach, push sensor deployments from well-funded flagship parks toward smaller reserves and citizen-science networks, widening who can run monitoring programs.
Third-order effects
- If benign surveillance over the natural world scales as the piece suggests — satellites down to smartphones listening for chainsaws — conservation becomes a standing data-infrastructure problem, inheriting the same questions about surveillance scope and misuse that visual-surveillance coverage has tracked since 2018.
- The pattern points toward shared sensing commons — open tools, public image archives, common hubs — becoming critical infrastructure for climate and biodiversity policy, with funding and governance following the data rather than the fieldwork.
The trend: Environmental monitoring is consolidating into always-on IoT surveillance networks that pair cheap sensors and open software with carrier connectivity, turning conservation into a data-infrastructure discipline.