Robot Sweeping is an Access to Future Smart Home

The capital market is optimistic about sweeping robots

ByteBridge.io
5 min readApr 1, 2022
https://zhuanlan.zhihu.com/p/133937902

In 2020, the robotics industry raised 242 financings cases with a total amount of 26.7 billion RMB(4.18 billion USD), of which sweeping robots accounted for 13%. In October 2021, there were more than ten financings cases in sweeping robots. As far as we know, the cleaning robots complete financing of more than 10 million RMB(1.57 million USD)each month.

The reason for the explosion of the sweeping robot

1 Large demand

The low-level desires and needs of all Generation Z, post-80s and post-90s, are the same. They need to become “lazier” and need to free their hands. When there is some improvement in product strength, such as cleaning rag service appear, the price can be raised higher, and the phenomenon of shortage of supply will occur as well.

2 The supply chain is mature

After large-scale industrial applications, the cost of some core components has been rapidly reduced. For example, advanced technologies such as self-driving cars and parts can be applied to the products like sweeping robots.

3 Product upgrade iterations

Large-scale cost reduction and product upgrade iterations triggered by the new generation of technology have catalyzed the industry’s explosion.

Price determines product power in many cases

“Now the price is still too high. From the perspective of many consumer products we have invested in, the gap ( 20% or 30%)between prices has a great impact on the result of the final sales.” An investor said. In addition, robot vacuum cleaners have more functions to develop in the future.

Many Internet of Things uses WiFi to connect various home appliances, most of which are pseudo-needs, including smart speakers. In the future, there will be only two entrances — One is a sweeping robot because it may be used every day and has enough household data, the other is a robot pet.

Robot sweeping is still a product of tomorrow

There is a difference between sweeping robots and many products. The comprehensive threshold is very high, and the threshold of algorithm and navigation must be surpassed before it can become qualified.

The core principle of the sweeping robot is to meet the user’s demand. In addition to mopping, there are many functional pain points, for example, the cleaning in the corners. These functional pain points need to be overcome and need to be innovated.Therefore, the maturity of the sweeping robot is still a long time to go.

The demand for data labeling continues to increase

From the perspective of the research direction of artificial intelligence technology, whether in the field of traditional machine learning or deep learning, supervised learning based on training data is still a major model training method. Especially in the field of deep learning, more labeled data is needed to improve the effectiveness of the model.

At present, the demand for the highest quality AI training data in various industries is urgent. AI is implemented in various fields, such as education, law, intelligent driving, banking, and finance, etc. Each field has requirements for subdivision and specialization.

Among them, in particular, traditional enterprises with intelligent transformation and technology enterprises need the assistance of training data service providers with rich project experience to help sort out the data labeling instruction and to obtain more suitable data. The use of high-quality data in special scenarios reduces the research and development cycle, accelerates the implementation process, and helps enterprises to make faster and better intelligent transformations.

ByteBridge.io, a Human-Powered and ML-powered Data Annotation Platform

ByteBridge, a data labeling tooling platform with real-time workflow management, provides training data for the machine learning industry.

Accuracy Guarantee

  • ML-assisted capacity can help reduce human errors by automatically pre-labeling
  • The real-time QA and QC are integrated into the labeling workflow as the consensus mechanism is introduced to ensure accuracy
  • Consensus — Assign the same task to several workers, and the correct answer is the one that comes back from the majority output
  • All work results are completely screened and inspected by the machine and human workforce
ByteBridge: a Human-powered and ML-powered Data Labeling SaaS Platform

In this way, ByteBridge can affirm our data acceptance and accuracy rate is over 98%.

Communication Cost Saving

On ByteBridge’s SaaS dashboard, developers can start the labeling projects by using the labeling instruction template and get the results back instantly.
From online setting labeling briefing to expert support alongside, the instruction communication is not that hard anymore.

ByteBridge Labeling Instruction Template

Configure Your Own 2D Images Annotation Project

  • Developers can control the labeling project from setting labeling instructions to output review on a pay-per-task model with a clear estimated time and price
  • Real-time management and monitoring of project
  • Real-time Outputs: clients can get real-time output results through API. (We support JSON, XML, CSV, etc. And we can provide customizable datatype to meet your needs)
ByteBridge: a Human-powered and ML-powered Data Labeling SaaS Platform

These labeling tools are already available on the dashboard: Image Classification, 2D Boxing, Polygon, Cuboid.

We can provide personalized annotation tools and services according to customer requirements.

Cost-effective

A collaboration of the human-work force and AI algorithms ensure a 50%lower price compared to the conventional market.

NLP Service

We provide different types of NLP in E-commerce, Retail, Search engines, Social Media, etc. Our service includes Voice Classification, Sentiment Analysis, Text Recognition and Text Classification(Chatbot Relevance).

Partnered with over 30 different language-speaking communities across the globe, ByteBridge now provides data collection and text annotation services covering languages such as English, Chinese, Spanish, Korean, Bengali, Vietnamese, Indonesian, Turkish, Arabic, Russian and more.

End

“High-quality data is the fuel that keeps the AI engine running smoothly. The more accurate annotation is, the better algorithm performance will be” said Brian Cheong, founder, and CEO of ByteBridge.

If you need data labeling and collection services, please have a look at bytebridge.io, the clear pricing is available.

Please feel free to contact us: support@bytebridge.io

Source: https://www.robot-china.com/news/202111/23/68486.html

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