 Well, the United Arab Emirates has been a committed supporter to WISIS and this year 2015 is no exception. With me from the UAE, I have Nabil Al-Zarouni. He is the Deputy Director of the Information Technology Department. Mr Al-Zarouni, hello. Hello. Thank you very much for coming today. Now you've been involved in developing the smart inspection system for the Ministry of Labour. What is that system and why do you think it's important? Okay, smart inspection system at the beginning, it's an electronic system that was designed and developed within the Ministry of Labour to automate the process of labour inspection. We had certain challenges earlier. We have a limited number of resources when we talk about human resources and other resources. Okay, and we have growing, I mean business is really growing in UAE. We have almost 300,000 establishment and it's keep increasing. We have almost like 4 million labourers or manpower working in UAE. So there was a need to overcome those challenges and make sure that whatever rules, federal laws for labour, all regulations that are set by Ministry of Labour are there in place and really implemented in a proper way. Okay. That's why we came out with this idea, with this system, which is the labour inspection system, the smart inspection system. What it does mainly, it collects some information from different systems with internal systems, with the Ministry of Labour or external government systems. It analyses those information and then it sets some sort of, what we call a risk level for each establishment or for each company based on the information gathered from different systems. And what we call those informations, usually we call them risk factors or risk influencing. For example, I'll give you a small example, a trade license expiry. If the trade license expired, we gave that factor some weight and based on that weight, we do some sort of calculation and then we decide, or the system decide on which risk level that establishment will go. Based on that, the inspection mission will be prioritized. So there will be some priority because again, we have only 400 inspectors and we have 300,000 plus establishments. So you needed those inspectors to be as efficient as possible. Exactly. So how did this system, with its rather automated processes, how did this improve productivity, or did it improve productivity? Yes, it did. It did. Initially, I mean earlier what used to happen is that the inspectors, they used to go to do inspections on companies or establishments or projects either randomly or they go and target certain establishments. But without having some, without having the information needed, whether there might be a possible risk on those establishments or not. So they might go on a visit or an inspection visit and then they found out there was nothing on that establishment. So they come out from there with a zero result. Waste of time. Waste of time, exactly. So what we did, we built that system with a powerful data analysis module within the system so we know when to send an inspection task to inspectors in order to target, and again I'm saying target certain establishment where we have a possibility of a risk. So doing so, we would be able to cover the risky establishment and slowly we go level by level down to address the other establishment. I understand. All right. So the system helps you establish priorities? Exactly. Okay, so what future enhancements do you have in mind for the smart inspection project? One of the future enhancements that we thought for the coming release of smart inspection is the forecasting. So we add some forecasting within the system to forecast based on certain trends, based on certain information, based on historical information that we gather for some years that okay, we might face a problem in establishment of type A. With the nationality of, for example, certain nationality, there might be a possibility or high possibility of risk in that establishment. So that's one of the future enhancements. Another one, we want to add the simulation or simulator capability within the system. So what we can do with the simulator capability, all those risk factors or all those information that we receive from different systems, internal or external, they have their own weight. And that weight can be increased or decreased or can be tweaked based on certain requirement. What we can do with the simulation, if we have a simulation, is that whenever we increase a weight of certain factors, we can simulate it on all the establishment information we have in the system. So we can, for example, know, okay, if we increase the weight to 20 instead of 10, the number of inspection visits will be more. Okay, so you've done a computer modeling. Exactly, some sort of computer modeling, some sort of what we call even the machine learning. Okay, so we are doing some sort of a machine learning in order to ensure that whatever risk factors, whatever weights has been assigned to those risk factors are realistic. I understand. Well, I thank you for your time today, sir. And Nabil Al-Zarouni from the Ministry of Labour, thank you very much. Thank you.