40 % Efficiency Increase: Cloud Computing and Scheduling

The book explains how to use cloud-based task management technology to improve labeling efficiency by 40 %, including resource allocation strategies, automation tool integration, and a guide to avoiding common problems. It helps teams quickly achieve efficient collaboration and task management.

Why choose cloud-based task scheduling?

Anyone who has done data annotation knows how painful it is to deal with uneven task allocation, idle resources, and difficult progress tracking.Last year, when we used the traditional method of scheduling, we often ran into situations where some people were sitting around waiting for tasks, while others were working overtime.Later, they tried introducing a cloud-based scheduling system, which boosted overall efficiency by 40 %.Here are a few of the most effective methods.

Three key steps in a real battle.

Task allocation and prioritization.

Don't just dump everything into the system at once! We've learned the hard way that some complex tasks can clog up the system, leaving simple tasks waiting in line.The first step is a "three-tiered method of dismantling.

1. Group annotations by type (e.g. rectangular frame / polygon).

2. Attach red, yellow, or green labels according to the urgency of the case.

3. Estimate time required for a task, and adjust dynamically.

The system will automatically assign higher priority tasks that require less time to idle personnel, just as a smart parcel sorting system does.

Dynamic resource allocation.

You've encountered situations where the equipment of the taggers has been slow, which has affected the progress of the work, right? Now we've deployed the tagging tool on a cloud server, and you can operate it through a browser.For example, if annotator A's computer suddenly crashes, his tasks will automatically be transferred to annotator B's terminal and the progress bar will not be interrupted.This saved the company at least 15 hours a week in lost time due to equipment malfunctions.

Automated quality control

The most surprising thing was the automation of quality control.When a task is submitted, the system automatically triggers a quality assurance script. If the task is found to be below 85 % correct, the system automatically sends it back, while at the same time sending the annotator examples of common errors.The return rate has dropped from 35 % to 12 %, and the quality control department no longer has to work overtime every day looking for problems.

These pits are not to be stepped in.

When we first started using the cloud to schedule production, we did take a few wrong turns.For example, in the blind pursuit of "total automation," the system sent mammal images to a group that specialized in architecture. Another time, they forgot to set a time limit for a task, and the delay slowed down the entire project.I suggest that everyone retain a manual review process for the initial period, and make minor adjustments to the rules for distributing work based on the data from the system every week. After all, even the smartest system still needs to be adjusted according to human experience.

The results are then compared.

Three months after going online, the data showed that average processing time per task had dropped from 4.6 hours to 2.8 hours, and the average daily effective working time of the labelers had increased by 3.2 hours.The most important thing is that project managers now have two hours a day to do strategic planning, rather than being busy playing "fireman.If you want to get your team out of the mess that is chaotic task allocation, you might want to try this cloud-based production-scheduling solution.