Proxmox with Debian containers.
About this report
Methane is responsible for around 30% of the rise in global temperatures since the Industrial Revolution, and rapid and sustained reductions in methane emissions are key to limiting near-term global warming and improving air quality. The energy sector – including oil, natural gas, coal and bioenergy – accounts for over a third of methane emissions from human activity. The IEA’s Global Methane Tracker is an indispensable tool in the fight to bring down emissions from across the energy sector.
This year’s update provides our latest estimates of emissions from across the sector – drawing on the more recent data and readings from satellites and ground-based measurements – and the costs and opportunities to reduce these emissions. It also tracks current pledges and policies to drive down methane emissions and progress towards these goals. For the first time the Tracker includes the investments needed to deliver emissions reductions and the potential revenue from these measures.
Published March 2024
License CC BY 4.0 Press release Share Cite Online table of contents
1.0
Key findings
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2.0
Understanding methane emissions
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3.0
What did COP28 mean for methane?
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4.0
Methane emissions in a 1.5 °C pathway
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5.0
Tracking pledges, targets and action
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6.0
Progress on data and lingering uncertaintiesThe small drones do not require a long range use, since you are going to detect them only late, and need to terminate them within few seconds.
I have seen an improvised optics on a Youtube channel where a 2 kW continuous operation fiber laser had enough energy flux at 100 m or farther.
The point of modern deep learning approaches is that they're extremely easy on the developer skill. Decades ago realtime machine vision needed a machine vision expert, these days you throw the hardware at the problem at learning stage, and embedded devices to run the results are stupidly powerful (doesn't even take a Jetson board), if you compare to what has been available even a decade ago.
Realtime person detection and following it with a drone? Difficult for me, certainly, but there are enough people out there who have done it.
There are cheap continuous operation 2 kW fiber lasers for material processing which could be enough for the flimsier slower drones.
In terms of bucks per kill the West is doing an order of magnitude worse.
I am aware. The 3 mm calibre difference has no impact on fabrication costs.
I know it already does, at least in newer Lancets. Expect this in fpv type devices soon.
These small drones attack single people and small infantry groups as well as small vehicles up to heavy armor. With laser there is the issue of portability, especially power supply. Also cheap reflective coating requires very high power densities for a kill. Apart from detection and tracking which can use fused microphone array and camera array data the time to react is very short and it has to provide high density of fire on the cheap. I've seen some shotgun use with very limited effectivity. Ditto nets. Maybe antidrone swarms can work, but power limits loitering time. Swarm attacks can easily overwhelm protection.
It looks like a hard problem.
It's a NUC so sufficiently poweful. Proxmox isn't fat by any means. If you run your stuff in containers then Proxmox (I aways install it on top of Debian) is your hypervisor is your base system. You typically don't install stuff on your hypervisor, though I do some very select things.