Tech
What is OSINT and why is it so useful
Let’s start by looking at the definition of OSINT. It is an acronym for Open-Source Intelligence. It encompasses information gathered from publicly available sources both offline and online. Offline OSINT sources can be public registers, public libraries, and archives open to the public, as well as news reports, search engines, online databases, social media networks, blog posts as well as public government data, academic publications, and even television reports, online videos, and public speeches (e.g., TED talks). In short, internet data that is publicly accessible. Although OSINT can provide valuable insights, the information is spread out across a large number of open platforms and sources, which makes collecting and analyzing these use amounts of data not only time-consuming, but also puts a strain on human resources. That’s why law enforcement, HLS, and security services are looking at using OSINT tools to get actionable insights quickly and accurately.
By using an OSINT tool, law enforcement, HLS, and security services do not have to handle the time-consuming and tedious job of gathering information from a vast range of sources anymore, which allows them to concentrate on other aspects of the investigation. Apart from the convenience, another important benefit of using OSINT tools is preventing information overload. When gathering big data, the volume of intelligence that these agencies need to go through is unprecedented and humanly impossible to be accomplished in a short timeframe. The OSINT tool allows for gathering and analyzing these vast amounts of data in the shortest amount of time possible, resulting in detailed intelligence that can be used for taking action.
In order to achieve this and to save time and resources, only the best OSINT tools should be used to prevent an investigator from being detected when gathering intelligence from OSINT sources. The solution of Cobwebs ensures that investigators remain anonymous and the search that they are conducting cannot be traced back to them. This ensures the personal safety of an investigator who is e.g., investigating a ruthless human trafficking gang. It also ensures that such gang members will be alerted about the investigations and will get rid of evidence that could have been used against them.
The automated web intelligence capabilities of a best-of-breed OSINT tool (e.g., Tangles of Cobwebs) allow authorities to locate certain threat actors with limited public information as well as locate other threat actors in that same online network. The OSINT tools can also carry out specific in-depth searches for extracting specific information to establish the real identities of virtual threat actors and map group connections tied to a specific threat actor.
For the best performance, OSINT tools need to use artificial intelligence (AI) to harness advanced capabilities such as machine learning and natural language processing (NLP). Since investigators often need to conduct their investigations cross-border, they need to collect intelligence that is often in a foreign language (e.g., a hacker forum on the deep web in Chinese or Russian). NLP algorithms allow for collecting and analyzing such intelligence to get valuable insights since the meaning behind the posts of a certain threat actor can be understood, and sentiment analysis can be performed to map the feelings of that threat actor towards certain topics. This valuable intelligence can be used to e.g., prevent a peaceful demonstration from turning into social unrest.
It is important to understand that AI capabilities do not only assist during the recon and data collection phase but are also extremely valuable for data analysis, which in turn is crucial for getting insights for follow-up.
To conclude, by utilizing OSINT tools in an easy-to-use AI web intelligence platform like Cobwebs Technologies’ Tangles, investigators can scour all levels of the internet as well as various social media platforms to gather open-source intelligence. This enables them to obtain precise and unrivaled web intelligence from the surface, deep, and dark web in a fraction of the time that it normally would take. This will save them precious time and speed up their investigations and even take action to prevent the next heist or terrorist attack.
Electronics
Delay Lines Compared: Coaxial, Acoustic, Digital and Fiber Optic Options for RF Systems
| Key Takeaways
• A delay line holds back an RF signal for a precise time and is used for radar and altimeter testing, signal-path alignment, phased-array beamforming and signal processing. • The four main delay line families are coaxial cable, acoustic (SAW and BAW), digital (ADC, memory and DAC) and fiber optic. • Coax and fiber add a similar delay of roughly 4 to 5 ns per meter, but single-mode fiber loses well under 1 dB per kilometer regardless of RF frequency, while coax loss rises with length and frequency. • Emulating a radar target at 10 km needs about 66 microseconds of round-trip delay, or roughly 13.6 km of single-mode fiber. |
What is a delay line?
A delay line is a component that holds back an RF or microwave signal for a precise, known amount of time and then releases it otherwise unchanged. Delay lines are used to emulate distance in radar and altimeter testing, to align the timing of parallel signal paths, to build true-time-delay beamformers for phased arrays and to provide short-term signal memory in correlators and receivers.
In radar work the delay always represents a round trip, which makes the numbers grow quickly. A SPIE conference paper comparing microwave analog delay line technologies points out that emulating a target only 50 m away already calls for 333.33 ns of delay, because the signal has to travel out and back. For readers who want the underlying vocabulary first, a broader primer on delay lines covers the terms used throughout this comparison.
What types of delay line are available?
There are four main families of RF delay line: coaxial cable, acoustic (surface or bulk acoustic wave), digital, and fiber optic. Each creates delay in a physically different way, and that physical mechanism determines its loss, bandwidth, size and flexibility.
| Technology | How the delay is created | Main strengths | Main limitations |
| Coaxial cable | The RF signal travels through a coiled length of coax, often semi-rigid | Simple, passive, no signal conversion | Bulky at long delays; loss rises with length and frequency |
| Acoustic (SAW / BAW) | RF is converted into an acoustic wave in a piezoelectric material, which travels far slower than an electromagnetic wave | Very compact for a given delay | High insertion loss, reported above 30 dB; SAW limited to roughly 2.5 GHz |
| Digital | The signal is sampled by an ADC, held in memory and regenerated by a DAC | Delay is programmable and can be combined with synthetic Doppler or modulation | Bandwidth and spurious performance set by the converters; adds latency of its own |
| Fiber optic (ODL) | RF is modulated onto light and delayed by a chosen length of single-mode fiber | Low loss that does not change with RF frequency; delays from nanoseconds to milliseconds | Requires optical conversion, which adds noise; each delay value needs its own fiber length or a switch path |
How do coaxial delay lines compare with fiber optic delay lines?
Coax and fiber produce a similar delay per meter, around 4 to 5 nanoseconds depending on the cable dielectric, but fiber achieves it with a tiny fraction of the loss. Standard G.652.D fiber has a group index close to 1.468, which works out to roughly 4.9 ns of delay per meter, or about 4.9 microseconds per kilometer.
The difference shows up in attenuation. A microsecond of delay needs roughly 200 m of either medium. Published attenuation tables put even thick 7/8-inch hardline at about 2.1 dB per 100 feet at 2.4 GHz, which means close to 14 dB of loss over 200 m, and thinner coax several times more. The same 200 m of single-mode fiber loses well under 0.1 dB of optical power. Just as important, the fiber loss is set by the optical wavelength rather than by the RF carrier riding on it, so the fiber in a fiber optic delay line contributes the same loss at 1 GHz as at 18 GHz, while a coax delay line becomes progressively lossier as frequency rises.
Longer delays make the gap decisive. The chart below shows how much fiber a radar test needs to emulate targets at different ranges. A 10 km target already requires about 13.6 km of fiber, a length no coax delay line could realistically match.

When do acoustic or digital delay lines make more sense?
Acoustic delay lines make sense when space is tight and the signal sits below a few gigahertz, and digital delay lines make sense when the delay must change continuously or the test needs synthetic signal effects. Acoustic devices exploit the fact that a mechanical wave in a piezoelectric crystal moves far more slowly than an electromagnetic wave, so a long delay fits in a small package. The cost is high insertion loss and, for surface acoustic wave parts, an upper frequency limit of around 2.5 GHz; bulk acoustic wave technology extends the achievable delay range.
A university study of wideband delay lines for automotive radar compares these approaches for a target simulator that needed an 800 MHz bandwidth and delays tunable from 1.3 ns to 1.67 microseconds, a useful example of how bandwidth and delay range together narrow the technology choice. Fully digital delay lines take a different route: an analog-to-digital converter samples the signal, memory holds it, and a digital-to-analog converter regenerates it. That flexibility is valuable, but instantaneous bandwidth, dynamic range and spurious content all depend on the converters.
What is the difference between fixed, variable and progressive delay lines?
A fixed delay line provides one delay value, while a variable delay line lets the user switch between several delays; a progressive delay line is a variable design that combines a small set of fiber spools in different combinations to produce many more delay values than it has spools. A passive optical delay line is simply a coil of fiber cut to an exact length and needs no power; in an RF system it sits between an optical transmitter and receiver.
Progressive designs typically use cascaded optical switch matrices. Four 2×2 optical switches can select 16 different delays, and eight binary-weighted spools can produce 255 distinct non-zero combinations. Variable, progressive and passive optical delay line architectures are explained in more detail, including how dispersion compensation and optical amplification are added when delays become very long.
How should an engineer choose a delay line?
Start from the application’s frequency range and maximum delay, then check loss, noise and switching requirements against each technology. The following criteria narrow the choice quickly:
- Frequency range: acoustic devices suit lower bands, while coax and fiber cover microwave frequencies and fiber holds its loss steady across them.
- Maximum delay and resolution: delays beyond a few hundred nanoseconds favor fiber; fine, continuously adjustable steps favor digital or switched designs.
- Insertion loss and noise figure: acoustic parts lose the most signal, while optical links trade a fixed conversion loss for nearly flat loss with length.
- Signal purity: phase noise and spurious content matter for radar and altimeter testing, where the delayed signal must look exactly like a real echo.
- Switching and control: test benches often need several delay values selectable from a front panel or remotely.
For signal-purity questions in optical designs, an application note on phase noise and RF amplification in ODL systems covers how amplifier placement affects the delayed signal. For catalog-level comparison of ranges and switch configurations, fiber optic delay line hardware shows how commercial units package these options into rack-mount systems.
Frequently Asked Questions
What is a delay line used for?
A delay line holds back an RF signal for a precise time, which is used to emulate target distance in radar and altimeter testing, align signal paths, steer phased-array beams and store signals briefly for processing.
How much delay does one meter of optical fiber add?
One meter of standard single-mode fiber adds roughly 4.9 nanoseconds of delay, based on a group index of about 1.468.
Why are fiber optic delay lines preferred for long delays?
Fiber optic delay lines are preferred for long delays because single-mode fiber loses well under 1 dB per kilometer and that loss does not change with the RF frequency being delayed, while coaxial cable loss grows with both length and frequency.
What is a progressive delay line?
A progressive delay line combines a small set of fiber spools through optical switches so that many delay values can be selected; eight binary-weighted spools can produce 255 different non-zero delays.
Tech
Drone Video Streaming for Public Safety: How the Live Feed Gets From the Air to the Command Post
| Key Takeaways
• Drone video streaming sends a UAV camera feed to command staff, dispatchers, and officers in real time, usually over cellular networks. • Chula Vista, California launched the first U.S. drone as first responder program in 2018 and passed 20,000 missions by July 2024. • In that program, drones reached the scene before patrol officers 14,830 times, arriving in an average of 92.75 seconds on those calls. • Combining several cellular connections into one stream reduces the risk that a single congested network interrupts the feed during an incident. |
What is drone video streaming in public safety?
Drone video streaming in public safety is the real-time transmission of a UAV’s camera feed to the people managing an emergency, including command staff, dispatchers, real-time crime center analysts, and officers on their way to the scene. The aim is to give responders eyes on an incident before anyone arrives on the ground.
The model most agencies now study is the drone as first responder, or DFR, program. Instead of launching a drone after officers are already on site, a docked or rooftop drone is sent the moment a 911 call comes in, and its live feed shapes how the rest of the response unfolds. Vendors and integrators have built video workflows designed for drone as first responder programs around that idea, treating the stream as the product and the aircraft as the delivery vehicle.
The practical setup varies by aircraft. Some enterprise drones output video over IP, others over HDMI from a ground controller, and a walkthrough of taking a docked enterprise drone live shows how a compact field encoder can sit between the drone’s video output and the agency’s command center or field devices.
Why does the live feed matter more than the flight itself?
The live feed matters more than the flight because the value of a first responder drone comes from what officers learn before they arrive: which route to take, how many units to send, whether special equipment is needed, and sometimes whether anyone needs to respond at all. Without a stable stream, a fast drone delivers very little.
The clearest public data comes from Chula Vista, California, where the police department began flying drones to emergency calls in 2018 in what it describes as the first program of its kind in the nation. According to the Chula Vista Police Department’s July 2024 program update, the program had passed 20,000 missions. The drone was first on scene 14,830 times, arriving in an average of 92.75 seconds on those calls, and patrol officers did not need to respond 4,336 times because of what the feed showed.
The department’s own examples show why. In one widely reported 2019 call about a man waving a gun, the drone’s camera revealed that the object was actually a lighter before officers made contact. In a 2023 car fire, callers gave the wrong location, and the drone operator used the live video to pinpoint the burning vehicle so officers could pull the driver out seconds before it was engulfed.

How does video get from a drone to the people who need it?
Video gets from a drone to responders through a chain of four links: capture, encoding, transport, and distribution. A weakness at any one of them breaks the whole feed, which is why agencies increasingly evaluate the chain as a single system rather than buying each piece separately.
- Capture: The drone’s gimbal camera, increasingly with thermal capability, produces the raw video at the scene.
- Encoding: An encoder, either on the aircraft, in the dock, or attached to the pilot’s ground station, compresses the feed so it can travel over a mobile network.
- Transport: The compressed stream travels over one or more cellular networks to a receiving server, usually in the cloud or at agency headquarters.
- Distribution: The server pushes the feed to the command center, the real-time crime center, video management systems, and browsers or phones carried by responders in the field.
Distribution is where many early programs struggled. A feed that only reaches the drone pilot’s screen does little for the sergeant deciding where to stage units. LiveU’s LU-REQON1, for instance, is designed to accept multiple IP and HDMI video inputs and pair with a browser-based return feed, so the same drone stream can reach a command center and an officer’s phone at once.
Why is a single cellular connection risky for drone feeds?
A single cellular connection is risky because emergencies tend to happen exactly where networks are under the most strain: crowded events, traffic collisions with onlookers, and large incidents that draw media and residents with phones. When that one connection congests, the drone keeps flying but the feed stalls.
Many drone deployments rely on single-carrier connectivity borrowed from body camera technology, which can struggle to hold a steady feed when that one network is busy. Bonded transmission takes a different approach by combining several cellular links, often across different carriers, into one stream at all times. If one network slows, the others carry more of the load without interrupting the picture. The trade-off is more hardware and more data plans to manage, which agencies weigh against the cost of losing visibility during a critical call.
What regulatory steps shape a drone streaming program?
In the United States, the key regulatory step is FAA authorization to fly beyond visual line of sight, known as BVLOS, because standard rules require operators to keep the drone in view at all times. A DFR program that cannot fly beyond line of sight cannot reach most of the calls it is meant to serve.
Chula Vista’s timeline shows how coverage expands as approvals accumulate. The department joined the FAA’s Integration Pilot Program in November 2018, became the first law enforcement agency authorized to fly BVLOS in an urban area in May 2019, with a range of up to three miles from the launch site, and added a second launch site that August. That second site covered about 33 percent of the city’s area but roughly 70 percent of its priority calls. By March 2021, the department had become the first in the country authorized to launch from anywhere in the city.
Each expansion increases the demand on the video link. More launch sites and longer flights mean more streams, over more varied terrain, reaching more endpoints, which is why connectivity planning tends to grow alongside the flight program rather than being settled once at the start.
What should agencies evaluate before choosing a streaming setup?
Agencies should evaluate latency, resilience under network congestion, integration with existing systems, and governance of how video is stored and shared. Image quality matters, but a sharp picture that arrives late or freezes mid incident is less useful than a steady, slightly softer one.
- Latency: Measure glass-to-glass delay from the drone camera to a responder’s phone, not just to the pilot’s screen.
- Resilience: Test during peak hours and at busy locations, since that is when real incidents strain networks.
- Integration: Confirm the feed can reach the real-time crime center, video management software, and mobile browsers without custom development for each.
- Governance: Set policies for retention, access, and privacy before launch. Chula Vista, for example, publishes historical flight data and states that it does not use DFR for proactive patrol.
Frequently Asked Questions
What is a drone as first responder program?
A drone as first responder program sends a remotely operated drone to an emergency call as soon as it is received, so its live video can guide officers and other responders before they reach the scene.
How fast can a first responder drone reach a scene?
In Chula Vista, California, drones that arrived before patrol officers did so in an average of 92.75 seconds, according to the police department’s July 2024 figures.
How is live video sent from a police drone?
Live video from a police drone is usually compressed by an encoder and sent over one or more cellular networks to a server, which then distributes it to command centers and responders’ devices.
Why do drone programs use bonded cellular connections?
Drone programs use bonded cellular connections because combining several networks keeps the video stable when one network becomes congested during an emergency.
Tech
How to Choose a Camera for Drone Surveying and Mapping
| Key Takeaways
• A camera for drone surveying needs a calibrated lens and sensor, accurate exposure timestamps and a shutter that does not distort images on a moving aircraft. • A global shutter exposes every pixel at once, avoiding the skew that rolling shutters create when a drone is moving. • Ground sample distance scales linearly with altitude; one 128MP payload is specified at 0.26 cm per pixel at 60 m and 0.52 cm per pixel at 120 m. • Because US Part 107 caps routine drone flights at 400 feet above ground, coverage gains have to come from sensor resolution and field of view rather than altitude. |
What makes a camera for drone surveying different from a consumer drone camera?
A camera for drone surveying is built to produce measurable data, which means a calibrated lens and sensor, an accurate exposure timestamp and a shutter that does not distort the image while the aircraft is moving. A consumer drone camera is built for video and attractive stills, and its small sensor, fixed lens and rolling readout are perfectly adequate for that job. For photogrammetry, corridor mapping or engineering-grade surveys, those same traits introduce errors that processing software then has to correct, or cannot correct at all.
Professional drone camera payloads built for survey and inspection are therefore sold as instruments rather than accessories. They typically come with a factory calibration, mount to specific aircraft through standard mechanical and data interfaces, and are rated against accuracy targets rather than just pixel counts.
Which specifications matter most when choosing a camera for drone mapping?
The specifications that matter most are sensor resolution and pixel size, shutter type, lens field of view, metric calibration, weight and how the camera talks to the drone. Each one feeds directly into how much ground a flight covers, how accurate the output is and whether the payload is practical on the aircraft the team already flies.
| Specification | What it controls | What to look for |
| Resolution and pixel size | Ground sample distance and coverage per photo | Higher pixel counts cover more ground at the same GSD |
| Shutter type | Geometric distortion on a moving aircraft | Global shutter avoids rolling-shutter skew |
| Lens field of view | Footprint width versus detail | Interchangeable focal lengths for different missions |
| Metric calibration | Systematic error in the final model | Factory calibration with a certificate |
| Weight | Flight time and platform compatibility | Light enough for the target airframe |
| Integration | Triggering, timestamps and control | Standard protocols such as MAVLink |
The P5, a 128MP survey payload designed for compact drones, illustrates how these factors come together in practice. It pairs a 128-megapixel medium format CMOS sensor with an electronic global shutter, offers 35 mm and 80 mm lens options, weighs under 700 grams and is factory metrically calibrated, with a calibration certificate supplied with each unit.
Why does a global shutter matter for drone surveying?
A global shutter exposes every pixel at the same instant, so a fast-moving drone produces an image with correct geometry instead of the skew a rolling shutter creates when it reads the sensor line by line. Early drone survey workflows sometimes worked around rolling-shutter distortion by slowing down or pausing for each photo. A global shutter removes that constraint, so the aircraft can hold a steady survey speed and the processing software does not have to model and remove a time-varying distortion in every frame.
The timestamp matters just as much as the shutter. Mid-exposure triggering records the moment at the center of each exposure, which lets GNSS positions be matched to images precisely. On a fixed-wing drone flying at well over 15 m/s, even a small timing offset translates into a positional error on the ground.
How does flight altitude affect ground sample distance?
Ground sample distance scales directly with altitude: double the height above ground and each pixel covers twice the distance, for the same lens and sensor. For the 128MP payload above, the published figures are 0.26 cm per pixel at 60 m and 0.52 cm per pixel at 120 m with the 80 mm lens, a near-perfect linear relationship that makes mission planning straightforward.

Altitude, however, is not a free variable. In the United States, the FAA’s Part 107 rules cap routine small-drone operations at 400 feet above ground level, roughly 122 m, require the aircraft to stay within visual line of sight unless a waiver is granted and apply to drones under 55 pounds. Because altitude is capped, a camera for drone mapping has to get its coverage from resolution and field of view rather than from flying higher. That is the core argument for medium format sensors on drones: more pixels across the frame means a wider footprint at the same legal altitude and the same GSD.
How much area can a high-resolution drone camera cover in one flight?
Coverage depends on GSD, overlap and the drone’s endurance, but higher-resolution cameras consistently cover more area per flight at a given GSD because each image is wider on the ground. Published figures for the 128MP payload list about 67 hectares at 60 m and about 135 hectares at 120 m, both at 70% overlap, which shows how coverage roughly doubles when altitude, and therefore GSD, doubles.
Pairing a lightweight high-resolution payload with a fixed-wing VTOL airframe extends this further, because fixed-wing aircraft fly longer and faster than multirotors while still taking off and landing vertically. The combination suits long corridors such as roads, pipelines and rail lines, as well as large construction sites where repeated surveys track progress over time.
How accurate can drone survey data be?
With a metric-calibrated camera, accurate timestamps and good ground control or GNSS correction, drone photogrammetry can reach sub-centimeter horizontal accuracy and around one centimeter vertically. For the 128MP payload discussed here, the stated absolute accuracy reaches 0.3 cm RMS horizontally and 0.8 cm RMS vertically. Figures like these always depend on the full workflow, including ground control, flight overlap and processing, so they are best read as what the camera makes possible rather than what every project will achieve.
Integration is the last practical check. A payload that supports industry-standard protocols such as MAVLink and Auterion, and that is already supported in common photogrammetry software, removes most of the custom engineering that otherwise sits between buying a camera and flying a production survey.
Which drone platforms suit a medium format survey camera?
Medium format survey cameras suit drones that can carry around 700 grams of payload with enough endurance to make use of the wider footprint, which in practice means larger multirotors and fixed-wing VTOL aircraft. Mounting flexibility matters here: the same payload may need to point straight down for area mapping or be configured for linear corridor surveys along roads and utilities.
Data handling is the other platform consideration. A 128MP camera producing several frames per second generates large files quickly, so onboard storage, here CFexpress cards of up to 2 TB, and a fast data interface, here 1 gigabit, determine whether a long mission can be flown without stopping to offload images. Checking these figures against planned flight durations avoids discovering a storage limit halfway through a corridor.
Frequently Asked Questions
What is the best type of camera for drone mapping?
For survey-grade drone mapping, a metric-calibrated camera with a large high-resolution sensor and a global shutter is generally preferred, because it produces accurate, distortion-free images at practical flight altitudes.
Does a drone camera need a global shutter for photogrammetry?
A global shutter is not strictly required, but it avoids the rolling-shutter skew that occurs when a moving drone captures an image line by line, which improves geometric accuracy and simplifies processing.
How high can a survey drone fly in the United States?
Under FAA Part 107, small drones are limited to 400 feet above ground level, or higher only when staying within 400 feet of a structure, unless a waiver applies.
How heavy is a medium format drone survey camera?
Medium format drone survey cameras have become light enough for compact drones; one 128MP survey payload, for example, weighs under 700 grams.
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