I think the detection time is rather important in enhancing the profitability of an airport. Assuming the four systems approved by FAA have the same FOD detection capability, a shorter detection time will allow the airport management to increase the frequency of aircraft take offs and landings, thereby enhancing the appeal and ultimately the profitability of that airport.

The bottom line of an FOD Detection System is to ensure the airport is safe for aircraft take offs and landings but a shorter detection will definitely help in enhancing the profitability of that airport

I did assume from the product page that the addition was the fact that the system could now distinguish birds from other FOD, and therefore deal with them differently, but it wasn’t entirely clear.

Thanks again for the clarification, I’m sure people will find it helpful.

Until the launch of Xsight’s BirdWize™, all FOD Detection Systems detected birds that landed on the runway as FOD. In many cases, a bird is a large object that suddenly appears on the runway. It can certainly be considered a foreign object. However, due to the transient and biological nature of birds, the industry and most specifically the airports handle birds differently than FOD. In many cases birds are under the responsibility of a different unit i.e. Wildlife Control Unit.

Now Xsight’s technology, with the BirdWize™ new capability, knows to automatically distinguish between birds and all other FOD. This capability is highly important to airports and the airport users. According to the FAA and USDA studies, in the civil market, 40% of the bird strikes happen at the surface height (i.e. the runway). It opens a variety of advanced procedures that I’ll not discuss here for obvious reasons.

BirdWize™ is a software package that can be installed alongside FODetect, utilizing the same hardware and infrastructure. Its not just a feature (as you said) which adds to FODetect® the ability to detect moving objects (which incidentally might be plastic bags, paper objects, vegetation and other types of transient FOD). It uses advanced image processing and object recognition techniques to automatically distinguish between birds and other objects and provide wildlife management both real-time and offline statistics about the existence, locations and numbers of birds on the runway.

Back to the names. RunWize™ is the name of Xsight’s Runway Management Solutions which is a suite of integrated technologies and products. RunWize™ provides an airport a set of automation and management tools for safer and more efficient runways. Fodetect® and BirdWize™ are different parts of the RunWize™ solutions and integrate with each other. FODetect® supports airport operators manage FOD, while BirdWize™ supports airport wildlife management manage bird hazards.

RunWize™ consists of additional technologies and be sure to hear more about them soon.

Hope this clarifies your questions.

Request matter
– Can we get estimate costs for installing Fodetect System?(per system)

Thank you! Good luck to you

“In summary, I completely agree with you i.e. that any FOD detection system has to have a database with the parameters that you describe. And that’s why, while in my previous role as Tarsier Product Manager, the first thing I did was to build one.

I actually have a presentation on exactly this subject which I plan on posting to Slideshare.net sometime soon.”

Did you ever post this presentation or do you have anymore information on this topic please?

Please i need your help.

Thanks,

Sergio.

Thanks for the comments, you state in your reply:

“Thus, in your example, you should assume (in some cases) that both slow and fast systems can detect with probability of 95%.”

Yes, I agree with you. I do try and make it clear that it is quite possible for systems based on different technologies to have a shorter detection time and a better probability of detection, when I say :

“So, does this mean that systems with a longer detection time are better?
No, I wish it were that simple, but it’s impossible to compare the trade-off between probability of detection and detection time across systems that are based on different technologies. It’s quite possible that a system based on one form of technology will have a better probability of detection, and a shorter detection time.”

Maybe I should have been clearer and stated that as well as the technology used, the configuration is also a factor. The aim of the article was not really to describe every factor that can be used to determine the absolute value of the key parameters, its aim was to demonstrate that detection time should not be the main design aim. Is having a short detection time good? absolutely yes, and if you can achieve this while maintaining a high probability of detection (by increasing the number of sensors, increasing radar power output, adding lights to camera based systems etc) then it is a very worthwhile pursuit.

The Risk Calculator spreadsheet (and now also a web page) takes this into account by allowing detection time and probability of detection to be entered as independent variables.

Thanks again for the comments.

Mark

First thing, I agree with you that detection time is not the “only” parameter for a FOD detection system and reducing FOD risk. It is obviously an important factor, together with probability of detection, False Alarm rate, visual interrogation capabilities, System availability in different weather conditions, etc. All these are all covered in the FAA’s AC, so nothing new here.

However, I have a technical comment regarding your analysis. Detection time is not only a sensitivity issue. That is, you claim that decreasing detection time would decrease detection sensitivity (or increase false alarm rate). I claim that detection time is also a function of the coverage area. The smaller the coverage area is, the faster it can be scanned. That is, a system using more sensors to scan the runway, can perform faster without impacting the detection performance. Thus, in your example, you should assume (in some cases) that both slow and fast systems can detect with probability of 95%.