LotusEye

0
0 Reviews
LotusEye offers AI-based anomaly detection that learns from normal sensor data and alerts on anomalies. Create models for free and upgrade if satisfied.
Added on:
Social & Email:
Platform:
Nov 09 2024
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LotusEye

LotusEye

0 Reviews
0
LotusEye
LotusEye offers AI-based anomaly detection that learns from normal sensor data and alerts on anomalies. Create models for free and upgrade if satisfied.
Added on:
Social & Email:
Platform:
Nov 09 2024
--

LotusEye Product Information

What is LotusEye?

LotusEye provides an advanced AI anomaly detection system that automatically learns patterns from normal sensor data. Users can easily create their AI models by uploading data, with no prior AI knowledge required. The platform is free to try, and offers rich features like email notifications, data uploads via API, and multi-member management. Anomaly detection is simple and effective in three steps: upload training data, upload test data, and review the anomaly scores. Free model creation allows you to verify its effectiveness before committing to a paid plan.

Who will use LotusEye?

  • Industrial engineers
  • Maintenance teams
  • Data scientists
  • IoT developers
  • Manufacturing units

How to use the LotusEye?

  • Step1: Upload training data of normal operations to create an AI model
  • Step2: Upload test data to check for anomalies
  • Step3: Review the anomaly scores calculated by the AI

Platform

  • web

LotusEye's Core Features & Benefits

The Core Features of LotusEye
  • AI model creation from sensor data
  • Free model creation
  • Email notifications
  • API-based data uploads
  • Multi-member management
The Benefits of LotusEye
  • No AI expertise required
  • Free to start
  • Immediate anomaly alerts
  • Rich feature set
  • Scalable based on needs

LotusEye's Main Use Cases & Applications

  • Industrial equipment monitoring
  • Predictive maintenance
  • IoT device management
  • Environmental monitoring
  • Data-driven anomaly detection

FAQs of LotusEye

What types of sensor data can be used?

We support wide-format and long-format CSV files with appropriate headers. Detailed formats are provided on our website.

How can I upload sensor data?

Upload via the service interface or drag and drop CSV files. Higher plans support API-based uploads.

When does the anomaly score become high?

The score increases when test data deviates from the learned normal behavior. Model accuracy depends on training data.

How frequently is the anomaly score calculated?

The score is calculated hourly. For shorter intervals, data is averaged over each hour before scoring.

Can only sensor data be used for anomaly detection?

No, any numerical data in CSV format can be used. Examples include server logs and system command outputs.

What payment methods are available?

We support credit card payments through Stripe.

I want to know more about how to use the service.

Refer to our detailed user manual available on the website.

Why is there a free plan?

The free plan allows users to verify the effectiveness of the system before committing to a paid plan.

How do email notifications work?

Users receive email alerts when anomalies are detected based on the predefined thresholds.

Do I need AI knowledge to use the service?

No, the system is designed to be user-friendly and does not require AI expertise.

LotusEye Company Information

  • Website: https://lotuseye.co.jp
  • Company Name: pratya, LLC
  • Support Email: NA
  • Facebook: NA
  • X(Twitter): NA
  • YouTube: NA
  • Instagram: NA
  • Tiktok: NA
  • LinkedIn: NA

LotusEye Reviews

5/5
Do You Recommend LotusEye? Leave a Comment Below!

Analytic of LotusEye

Visit Over Time

Monthly Visits
0
Avg Visit Duration
00:00:00
Page Per Visit
0.00
Bounce Rate
0.00%
Dec 2024 - Feb 2025 All Traffic

Traffic Sources Traffic Sources

Mail
0.00%
Direct
0.00%
Search
0.00%
Social
0.00%
Referrals
0.00%
Paid Referrals
0.00%
Dec 2024 - Feb 2025 Desktop Only

LotusEye's Main Competitors and alternatives?

  • AWS IoT Device Management
  • Microsoft Azure IoT
  • Google Cloud IoT Core

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