The European market for lightning data has providers from both the public and private sectors. In a few countries (Denmark, Finland, Portugal, Romania, Spain, Sweden, UK) the National Meteorological Services (MET) can provide lightning detection data. In most cases this is because of the incidence of forest fires or aviation. In countries where the METs don’t collect lightning data, METs buy this data from private market leading companies and they are usually not allowed to resell or distribute this data to end users. Both MET and private data is considered expensive for end users.Industries and other sectors sensitive to lightning frequently report problems caused by lightning impacts. Even with the best available lightning protection, goods are at risk of damage or burning. While new European norms were published to help reduce the effects of lightning, many older buildings do not incorporate such protections. Many sensitive infrastructures, such as airports, hospitals, sports stadiums, and telephone and power lines (for electricity distribution and railways) are often affected by lighting. Also, electronic components are particularly vulnerable to lightning-induced transient voltages. Lightning is one of the leading weather-related causes of deaths and injuries . There are roughly 2000 thunderstorms in progress around the world at any one time, producing about 30 to 100 Cloud-to-Ground (CG) flashes each second, or about five million flashes a day .Realizing the conditions on the current market with lightning data LoLight aims to provide for private meteorological stations/private weather companies an innovative, real-time, low-cost, user friendly and accurate sensor technology to localize lightning strikes. It will use data of detected strikes to track/monitor super-cells, thus predicting thunderstorm movements, which will help the companies to raise the level of their services and to have competitive advantage against big detection networks providing long-range (even global) detection coverage as they are intended to predict storm evolution and global risk, providing general data for statistical use.The objectives of the project are to develop a low-cost system for lightning detection with an accuracy of 100m (the error range of current systems is of some hundred meters in best case scenarios, typically kms ), super-cell tracking, prediction of lightning events in real time and total mapping with archive of recorded historical lightning data within 200 km. Thanks to the whole mapping of lightning and the fact that differences exist between the emitted electromagnetic radiation profile of CG and Intra-Cloud (IC) discharges the systems will ensure 99 % of identification of IC, CG and hybrid discharges.