MetaFactor’s Manual Data Entry App: One Powerful and Intuitive Tool

Overview

In the evolving landscape of industrial operations, the ability to capture accurate, timely data remains a cornerstone of operational excellence, especially when it comes to assets and systems that rely on consistent monitoring. While automated data collection from sensors and IoT devices has become the norm, manual data entry still plays a critical role in scenarios where automation is not feasible.

Manual Data Entry App: Smarter Field Operations
Recognizing this need, MetaFactor has developed a powerful, secure, and intuitive Manual Data Entry Application designed specifically for field operators, engineers, and technicians working within industrial environments. Whether you’re operating within AVEVA PI, AVEVA Historian Canary, or other historian platforms, this tool bridges the gap between manual observations and your real-time data ecosystem.

What Is the Manual Data Entry Application?

The MetaFactor Manual Data Entry Application is a platform-agnostic, lightweight tool that enables users to manually input tag data securely and efficiently into systems like AVEVA PI and Canary. Designed with usability, flexibility, and reliability in mind, it supports operations in remote environments where automation hasn’t yet been deployed or where validation of automated data is required.

Key Features

Platform Agnostic

Whether your organization uses AVEVA PI, Canary Labs, or a combination of historian systems, this application integrates seamlessly with your existing infrastructure. It supports standard tag data types and communicates directly with the underlying data architecture.

Mobile and Desktop Compatible

Built using responsive technologies, the application runs smoothly on both mobile devices (tablets, smartphones) and desktop environments, providing flexibility for field and control room users alike. It’s ideal for rugged field work and high-precision data collection on the move.

Installable and Fully Functional Offline

The Manual Data Entry Application offers powerful offline functionality. Users can install the app directly from their browser onto their mobile phone with a single click. Once installed, the application stores all necessary tag data, user inputs, and to ur configurations locally, allowing full use in remote or low-connectivity environments. Operators can enter data, scan barcodes, and complete inspection tours without an internet connection. When connectivity is restored, the app sends the data to the endpoint historian (such as AVEVA PI or Canary), ensuring data integrity and continuity. This capability makes it an ideal solution for field personnel working in challenging or isolated locations.

Simple, Intuitive Interface

User adoption is key. That’s why we’ve designed the interface to be minimal, efficient, and easy to use reducing training time and ensuring error-free data entry. Fields are auto-validated by datatype, clearly labeled, and structured to guide users step-by-step.

Barcode Reading Functionality

For assets equipped with barcodes or QR codes, users can scan directly from their mobile device cameras, automatically pulling up relevant tag collections, significantly speeding up the process and reducing input errors.

Supports All Common Tag Data Types

The application supports all standard data types, including:

• Numeric Types
• Boolean
• Strings
• Enumerations (Dropdowns)

This ensures that any type of field observation can be captured accurately. Support for images will be added soon, allowing visual data to be included alongside standard field inputs.

Tour Functionality – Structured Data Entry at Scale

Operators can create “Tours”, predefined sets of tags grouped by location, system, or operational context. Tours guide users through a consistent, repeatable data entry process, ensuring comprehensive coverage and easy timestamp synchronization.

Example: A maintenance technician performs a daily inspection tour on a pump station. The app walks them through each checkpoint, levels, pressure, temperature and ensures each value is logged with an accurate timestamp.