Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
There is no need to purchase hardware, alter your existing network, or deal with complex installations; just a straightforward setup of a small software library is required. By the year 2025, it is projected that a staggering 75% of all data generated by enterprises, which amounts to 90 zettabytes, will originate from Internet of Things (IoT) devices. For context, the total storage capacity of every data center globally is currently less than two zettabytes. Additionally, an alarming 98% of IoT data remains unprotected, highlighting the urgent need for enhanced security across all data. One major challenge for IoT devices is the limited battery life of sensors, with few immediate solutions available. Moreover, many users of IoT face difficulties related to the range of wireless data transmission. We believe that AtomBeam will revolutionize the IoT landscape in much the same manner that electric lighting transformed daily life. The addition of our compaction software can effectively address several critical barriers to adopting IoT technologies. With just our software, you can enhance security measures, prolong sensor battery life, and boost transmission ranges significantly. AtomBeam also presents a chance to achieve considerable savings on connectivity and cloud storage expenses, facilitating a more efficient IoT ecosystem for all users. Ultimately, the integration of our software could reshape how businesses manage their data and optimize their resources.
Description
The FireFly® Indoor Gunshot Detector is a wireless device specifically engineered for indoor use. Its installation process is straightforward, requiring only two fasteners to secure each sensor in place. The positioning of the sensors is crucial as it influences the area they can effectively monitor, with an unobstructed detection range potentially covering up to 31,415 square feet. This compact and battery-operated gunshot sensor autonomously performs a validation analysis to distinguish between actual threats and non-threats by utilizing advanced algorithms that assess energy levels and waveforms. Typically, the sensors are installed on horizontal ceiling surfaces, thereby achieving a detection coverage area of approximately 31,415 square feet. However, when mounted on vertical columns, the coverage area is notably reduced. The sensor transmits threat validation data wirelessly to the EAGL System Server through the EAGL Gateway, where the information undergoes further processing. This processing triggers the appropriate pre-programmed autonomous Adaptive Response features and protocols, ensuring a rapid and effective reaction to potential threats. Additionally, the integration of these systems enhances overall safety and security in indoor environments.
API Access
Has API
No
API Access
Has API
No
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
AtomBeam
Country
United States
Website
atombeamtech.com
Vendor Details
Company Name
EAGL Technology
Country
United States
Website
eagltechnology.com/firefly-indoor-gunshot-detector/
Product Features
IoT
Application Development
No
Big Data Analytics
No
Configuration Management
No
Connectivity Management
No
Data Collection
No
Data Management
No
Device Management
No
Performance Management
No
Prototyping
No
Visualization
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No