The mobile web version of Nokia Maps now looks and behaves more like a standard native application on Google Android and Apple iOS devices, thanks to HTML5: The navigation service now provides offline downloading of maps. This ability can reduce mobile broadband data charges or allow map usage in areas that have limited or no wireless data service.

Enthusiast site Android Community noted the updates on Monday by way of the HandHeld Blog. In addition to the downloadable maps, the service — found at http://m.maps.nokia.com — also adds public transit directions to supplement the existing walking and driving navigation as well as points of interest (POI) and guides to the local area.

Nokia’s mapping service is arguably one of the best software products to come from the Finland-based handset maker, and this update makes it even better. Why else would Microsoft decide to integrate Nokia Maps in the Windows Phone platform going forward? I used the web version of Nokia Maps earlier on Monday, finding it to be so full-featured that it was almost difficult to believe it to be a web application.

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The offline mapping mode is welcome, especially when many smartphone owners pay for set amounts of wireless data. Google, too, recently introduced downloadable maps, partially for this reason. Nokia’s implementation is somewhat limiting, though, at least in my short tests. The initial geographic area I wanted to map was too large, so Nokia Maps wouldn’t save it. I had to keep zooming and cropping before saving.

The end result was a reasonable size — about 15 square blocks of Philadelphia — and I had to boost the storage limits allocated to the service to get the 19 MB area map downloaded. Nokia calls these “neighborhood maps,” so if you’re planning to visit several areas, each neighborhood will have to be downloaded separately. That differs from Google’s solution, where I was able to grab a map of 10 square miles. Once you have a local map from Nokia stored on the device, you don’t have access to the guides and POIs, but you can zoom in for greater detail, just like Google’s version.

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When it comes to my iPhone (or any smartphone for that matter), the biggest frustration I have is when the phone switches between Wi-Fi and 3G networks and just hangs. The data connection enters a weird state of “hang.” The same catatonic network status returns when switching between two Wi-Fi networks. Instead of finding the strongest network, you are stuck on a network that is weak at best.

One would think by now we would have figured out this hand-off problem, right? Wrong. As more and more Wi-Fi networks come into our lives, the hand-off problems are becoming worse and worse. A group of researchers at Massachusetts Institute of Technology got so frustrated they started working on solving this problem.

In doing so, they’ve come up with a set of new communication protocols that use information about a smartphone’s movement to improve handoffs. In experiments with these protocols, they decreased the need of portable devices to switch networks by 40 percent and improved the throughput by 30 percent. These protocols bring about many other network improvements, but that’s not the story.

The Sensory Overload
The real story is how these MIT researchers — graduate student Lenin Ravindranath, Professor Hari Balakrishnan, Associate Professor Sam Madden, and postdoctoral associate Calvin Newport, all of the Computer Science and Artificial Intelligence Laboratory — used various mobile phone sensors such as GPS, accelerometers and gyroscopes and took that data to solve a problem.

Balakrishnan jokes that the protocols came as a result of their own annoyances with the network problems, but he’s hopeful these protocols are going to be widely adopted by others.

To me, this usage of sensors to build an application that solves a common problem offers a futuristic view of what mobile apps could do. And in the process, it could bring about higher level of engagement. Sure there are some apps — like some gaming apps on the iPad — that leverage the sensors on the device, but most apps today are still nowhere close to capitalizing on the capabilities of these devices.

So far, apps that use single-sensor inputs, such as the GPS, microphone or the camera, have generated tons of excitement. Now imagine many of these (and other) sensors working in tandem and the experiences created on top of this sensor mash-up.

In his research role, Balakrishnan had been involved in the Pothole Project, which essentially used the data from the sensors to figure out all the potholes in the Boston area and plotted them on a map. That’s a clever use of sensor data from mobiles for building a web-based application. Now imagine taking that entire sensor input and making it part of an app experience.

Philippe Kahn, a veteran entrepreneur and co-founder of MotionX, described this sensor-enriched environment: “The motion-aware mobile platform is the new media.” His company uses variants of the principles articulated by Balakrishnan in its apps such as Motion X-GPS and Motion X-GPS Drive.

Motion Magic
Balakrishnan doesn’t see why there couldn’t be other applications built that are able to decipher our common motions — walking, sitting, commuting — by taking data from various sensors. This activity layer built on top of sensors can provide much-needed context, and in the process, make apps more engaging and give them a touch of serendipity.

Jeff Jonas, an IBM researcher and one of the keynote speakers at our Structure Big Data conference, often says machines inside corporations need to understand the who-where-what-when-and-why in order to get a better grip on the explosion of data and benefit from it. The iPhones and iPads are no different.

The mobile phone is not made for textual interactions, but instead, it is one, which has similar visual and contextual capabilities as we have. To achieve that goal, the app developers need to think differently and use sensor data inputs as a core building block of their overall user experience, just as they do with the data that comes from the social graph.

When we think of mobile phones, we need to stop thinking of them as computer-like devices, and instead, think of them as extensions of us. The mobile machine in our hands needs to understand what’s happening in our lives and factor that into experiences based on those inputs. In a post last year, I asked the question, can mobile phones think?

If they don’t, they will soon becoming tools of interruption and thus annoyance –- much like the irritation felt by the MIT researchers when bad network handoffs prevented them from getting their email.