Helvar ActiveAhead® and OMS Lighting have formed a strategic partnership to pioneer the next generation of lighting control systems.
This collaboration combines HELVAR’s expertise in AI-powered, self-learning lighting solutions with OMS Lighting’s innovative lighting fixtures and systems.
Together, they aim to deliver cutting-edge, adaptive lighting solutions that enhance energy efficiency, user comfort, and operational efficiency.
OMS Lighting: https://oms.lighting
Helvar ActiveAhead®: https://helvar.com/activeahead/
Key features of Helvar ActiveAhead:
1. Self-learning system:
- The system uses machine learning algorithms to constantly adapt to changes in the environment.
For example, it learns from patterns of movement, daylight availability and occupancy to optimize lighting levels and ensure that energy is consumed only when it is needed.
2. Wireless connectivity:
- ActiveAhead devices communicate wirelessly, simplifying installation and reducing the need for extensive cabling. This is especially beneficial when retrofitting existing buildings.
3. Motion sensors:
- The use of motion sensors is a key component of Helvar ActiveAhead. These sensors detect movement in the space and adjust the lighting accordingly.
For example, in a warehouse, lights can turn on when workers are walking through aisles and dim when the area is unoccupied, resulting in significant energy savings.
4. Data processing and triggers:
- The system collects data from sensors and uses it to create triggers for specific actions. For example, if the system detects that certain areas of the warehouse are frequently accessed, while others remain unused, it can suggest changes in layout or storage strategies to improve efficiency and utilization.
- Triggers can also be set for maintenance alerts, such as notifying facility managers when certain lights are used more frequently and may need servicing sooner.
5. Warehouse optimization and utilization:
- In addition to lighting, data from motion sensors can be used to optimize warehouse operations.
By analyzing movement patterns, the system can help reorganize the warehouse to ensure, that frequently used items are placed in more accessible locations, reducing time and effort for workers.
- This data can also be used to monitor overall warehouse space utilisation, helping managers identify unused areas or bottlenecks in workflows.
6. Energy efficiency:
- ActiveAhead's ability to dynamically adjust lighting based on real-world data means significant energy savings.
This is especially important in large facilities where lighting can be a significant cost.
By ensuring that lights are only on when needed and at the appropriate level, the system can significantly reduce energy consumption.
7. Scalability:
- The system is highly scalable, making it suitable for both small and large properties. It can be integrated into existing lighting systems or implemented as part of new installations, offering flexibility for different types of projects.
8. User interface and management:
- Facility managers can interact with the system through user-friendly interfaces that allow them to monitor energy consumption, occupancy patterns and other critical metrics. This data can be used to generate reports and make informed decisions about facility management.
Practical applications:
- In warehouses: ActiveAhead can help optimize layout and storage by leveraging data from motion sensors to track how space is being used.
It can also provide efficient lighting management, leading to cost savings and improved working conditions.
- In office spaces: the system can adjust lighting based on occupancy and available natural light, thus creating a comfortable working environment while minimising energy consumption.
- In industrial facilities, ActiveAhead can increase safety by providing, ensuring that work areas are well lit when occupied and reducing the risk of accidents.
In short, Helvar ActiveAhead harnesses the power of data processing, machine learning and sensor technologies to create smarter and more efficient environments. The system's ability to generate actionable triggers based on real data makes it a valuable tool for optimizing operations, especially in large dynamic spaces like warehouses.
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