MGC - Machine Generated Content

In this article, I'd like to mention a new Web field, and check its posibility through some examples, and also to define its key factors.

As we know, the key feature of Web2.0 is User Generated Content, which shares a common feature with Web1.0, which is that: all content is generated by humen intentionally, and the data has already got its meaning after being generated.

As now Android-Inside mobile phones and devices are getting popular, this new trend might lead us into a new Web field, which feature is that: the meta data was generated or collected by machines(mobile phones, devices, etc) originally, the data got its meaning only after being processed in remote data center. For this field, I call it MGC, which is Machine Generated Content.

Now let's take some examples to help to understand, although they're might not be possible in the next couple of years.

Example 1: Health application.

Scenario: John suspects that his heart is not funcitoning well, so he wears a special watch for a week. Actually this wathc is a Android-Inside device, which can monitor and record his pulse and blood pressure in real time. The data will be sent to hospital every night. The data center will analyze it and generate a report after all data being received. Doctor will check the report and take it as assitance for diagnosis.

Example 2: Traffic application.

Scenario: John's using Google navigator as other million drivers. The chip inside navigator collects car's data such as location and speed in real time, and send the data out to data center in real time. Data center will analyze all of data and then generate a summory traffic report, and then send the report into navigator's traffic layer. So while driving, John can get the road traffic information in real time, so that he can adjust his route according to it.

Example 3: Monitor application.

Scenario: John has a very yound child, so John concerns his safety when he's working in office, so he installed several smart cameras, which he can access through remotely, and each minute a snap shot saved into album automatically. If all of the cameras cannot find the kid in the visual angle, then an alert notificaiton will to send to him through email and short message.

Through above examples, we can find some features of MGC: 1. The collecting and processing of data can be isolated, data could be collected in local, while be processed remotely. 2. Data didn't have its meaning before analysis, so the data looks like device logs, most of them are kind of useless.

Now let's analyze some key factors of MGC.

Factor 1: data collecting.

Data collecting includes these methods:

1. Mobile APP - APP recall mobile's sensors such as GPS/Gravity/Atmospheric-Pressure to collect data.

2. Mobile Device - Device attached to mobile phone via USB/Audio ports, and convert data by algorithm.

3. Android-Inside Device.

Factor 2: data transaction.

I'd like to advise these 2 methods for small companies:

1. Use Twitter API as a protocal, to transfer data via Internet.

2. Use Amazon EC2, and install OpenSource MicroBlog software, so that you can setup your private transaction cloud.

With these 2 methods, we can transfer data through Internet in real time.

Factor 3: data processing.

Data processing includes core business logic.

Take the human body as a metaphor, the sensors inside the body surface and neurons collects data, the nervous system transfers data, and the brain processes data.

And as for a typical future MGC application, Android is its neuron, Twitter its nervous system, and its brain located in Goolge or Amazon's data center.