TGTGInsighttelegram intelligenceLIVE / telegram public index
← GZ学习频道

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @olddriverGDstudy · Post #51 · Mar 24

#上头诫#知识 噫吁嚱,呜呼哀哉。佳丽之心, 如渊似海云雾间。前有鬼者心有属,今有上将四人间。心似骄阳深似火,怎当白桓是真心。柳间戏水不得喻,错将弱颜当磐石。今日不见凄鬼之心散步言语现,此时却如千万金石尽如吼头甜。千言万语悬浮脑海间,百转千回纠缠心火炼。上将游戏四水间,怎奈四水通流涧。不得可可不得乖,碧水深潭心坏怜。心知真己不觉少,奈何四水风见消。索向索梁不觉走,回神已在深涧见。深涧云气鬼雾袅,崖山悬顶有佳囡。云烟做红霞,鬼雾做红妆。似是云波似是锦,可文鬼泣是有心。东升日出朝阳起,云散无效鬼泪去。不知南柯曾觉晓,梦里梦外梦惺惺。囡囡心念念,鬼鬼向戚戚。柳七窃窃似潇潇,新年却已入人牢。谁知何时却明晓,涉水不足总深腰。无问无知无所念,有情有景有春宵。尽知尽晓秀哥谣,不管不顾十诫飘。愿此流真做悲景,莫要上头惹人笑。

Results

2 similar posts found

Search: #geolocation

当前筛选 #geolocation清除筛选
Libreware

@libreware · Post #1512 · 09/28/2025, 11:58 AM

Chasing Your Tail (CYT) https://github.com/ArgeliusLabs/Chasing-Your-Tail-NG A comprehensive #WiFi probe request analyzer that monitors and tracks wireless devices by analyzing their probe requests. The system integrates with #Kismet for packet capture and WiGLE API for #SSID#geolocation analysis, featuring advanced #surveillance#detection capabilities. Features Real-time Wi-Fi monitoring with Kismet integration Advanced surveillance detection with persistence scoring Automatic GPS integration - extracts coordinates from Bluetooth GPS via Kismet GPS correlation and location clustering (100m threshold) Spectacular KML visualization for Google Earth with professional styling and interactive content Multi-format reporting - Markdown, HTML (with pandoc), and KML outputs Time-window tracking (5, 10, 15, 20 minute windows) WiGLE API integration for SSID geolocation Multi-location tracking algorithms for detecting following behavior Enhanced GUI interface with surveillance analysis button Organized file structure with dedicated output directories Comprehensive logging and analysis tools Requirements Python 3.6+ Kismet wireless packet capture Wi-Fi adapter supporting monitor mode Linux-based system WiGLE API key (optional)

djangoproject

@djangoproject · Post #241 · 01/25/2017, 01:30 PM

http://www.aparat.com/v/4yGhH #Geolocation apps with #Django. Latitude, longitude, altitude, and even #iBeacons can be leveraged to enable geo-targeted experiences. But how do we build and optimize the server-side components to handle these requirements? Using a combination of libraries and techniques, we will illustrate these concepts. In this discussion everything from #map clustering and caching, to distance calculations and polygonal layering will be demonstrated using Django, #GeoDjango, #Redis, and #PostGIS as our tool belt.