Empowering Smart Life Fields
through AI-Powered
Digital Transformation
Energy
AREYLight Reduces Energy Consumption using AI Ready
Conserve $12M out of $20M
Smart City
Reduce costs by predicting problems in advance or in real time with awareness struct
Green Buildings
Reduce costs by predicting problems in advance or in real time with awareness struct
Welcome to AREYTech AI
Welcome to AREYTech AI where we're constantly pushing the boundaries of what's possible with cutting-edge technology. We specialize in creating state-of-the-art solutions that leverage the power of artificial intelligence the internet of things and other advanced technologies to solve complex problems and enable real-time decision-making.
Our cutting-edge technology allows lighting units to be remotely controlled and optimized resulting in significant reductions in electricity usage. Through our wireless lighting controls and connected lighting management software we enable cities to become more autonomous and sustainable. With neural network communication our Smart Units form autonomous lighting groups that outperform any available solution on the market.
Join us in shaping a brighter greener future for citizens worldwide.
Redefine Energytech Conserve electricity usage by AI
Connected Smart Light Conrol
AREYLight provides proactive lighting control technology needed by vehicles and pedestrians.
Lights will intelligently turning on when light is required
And We make learn street lights when and how to use their powers
In this way, Energy is consume only as needed.
Explore Techs
AR
Smart City Solutions
We make learn lights when and how Use Their Powers
High Efficiency with Unmanned Light Control Units
AREYLight ensures that lighting units can be controlled remotely without the need for infrastructural change.
The solution makes cities autonomous while reducing expenses, returning on investments and efficiency. Smart units turn into Autonomous Lighting groups with neural network communication.
Our proprietary algorithms allow for affordable efficiency gains on a scale that could not be obtained before
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Predictive modeling: AI algorithms can be used to build models that predict the performance of LoRaWAN networks based on factors such as distance, terrain, and signal strength. These models can be used to optimize network parameters and improve coverage.
Real-time monitoring: AI algorithms can be used to monitor the performance of LoRaWAN networks in real-time, and adjust network parameters as needed to maintain optimal coverage and performance.
Network planning: AI algorithms can be used to analyze data on the physical environment and other factors, and generate optimized network plans that take into account factors such as coverage, capacity, and interference.
Self-healing networks: AI algorithms can be used to detect and diagnose network issues in real-time, and automatically adjust network parameters to maintain optimal performance
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