Projects that target aid toward villages and rural areas in the developing world often face time-consuming challenges, even at the most basic level of figuring out where the most appropriate sites are for pilot programs or deployment of new systems such as solar-power for regions that have no access to electricity. Often, even the sizes and locations of villages are poorly mapped, so time-consuming field studies are needed to locate suitable sites. Now, a team of graduate students at MIT and a social-service group of data scientists have come up with a way of automating parts of that evaluation process, by developing software that can identify houses and even types of houses from readily-available satellite imagery -- potentially saving considerable time that would otherwise be spent sending teams from village to village. Their findings have now been published in the journal Big Data. The multidisciplinary team came together in the course of discussions at MIT's Sidney Pacific graduate dormitory, explains team member Brian Spatocco: "We started talking about this problem, and we realized we all had skills that were relevant."

Buildings are the largest energy consumers worldwide, so it seems the sector is ripe for energy investment and savings potential. In order to reduce buildings' energy impact, strategies have been developed to help owners and tenants use technology more efficiently. Yet these strategies vary from residential or commercial buildings -- which combined make up more than 30 percent of final energy consumption across European Union member states. This is the scope for Henrique Pombeiro's PhD thesis for the MIT Portugal Sustainable Energy Systems program. For this research, Pombeiro has been awarded a Fulbright Research Grant that will allow him to continue his studies at MIT on how to improve energy efficiency in buildings.

For everyone who recycles their batteries, good for you! Your efforts won't be wasted, at least not in Sweden and the U.K., where a machine with artificial intelligence is being developed to sort all of those batteries so they can be sold for their still-usable components. University of Gothenburg, in Sweden, has a camera and a computerized brain that runs on a neural network. That kind of system works more like a human brain in that it can learn to "see" patterns and respond to them. It's an ability that's important for sorting batteries, which come in a range of different sizes and shapes and contain materials, such as lead, cadmium and steel, that need to be distinguished from one another because they're valuable for resale. At the recycling plant, batteries are fed to the machine on a conveyor belt.

Impossibly thin televisions, wireless HD video systems for the living room, and TVs that respond to gestures instead of a remote control were all things seen first at Ceatec, the annual gadget extravaganza outside Tokyo. The show's well-earned reputation as a peek into our gadget future remains intact as Ceatec 2010 kicks off Tuesday. It's guaranteed to be full of some of the geekiest stuff you've ever seen, along with some fantastically designed gadgets, and a mostly realistic look into what the rest of the world will some day be buying for their homes, backpacks, and cars. Oh, and there will be plenty of creepy robots too. The annual Japanese gizmo gathering will inevitably lead many Americans watching coverage from afar to ask, yet again: Why can't we get this stuff here?

TOKYO--Japan's robotics response to the disaster at the Fukushima Daiichi nuclear plant has been disappointing so far, but a 5-ton rescue robot developed after the 1995 Kobe earthquake may see some action at the facility soon. Created by Fukuoka-based Tmsuk in 2007, the T-53 Enryu (PDF) is a hulking, 9-foot-tall machine on treads with a bulldozer attachment and giant arms to move debris. Enryu (or "Rescue Dragon") is expected to clear highly radioactive rubble at the plant to provide machines and people better access, but it may need to be shielded with lead to protect it from radiation. It would be the second Japanese robot on the scene following a radiation detector robot, which apparently hasn't been used much. Each of Enryu's arms has six joints and can hoist about 220 pounds.

Korean children, already fast becoming a robot-friendly lot, have a new companion in Kibot, a monkey-faced bot that can read fairy tales, sing songs, take pictures, and make video calls via a display embedded in its tummy. Wireless operator KT Telecom started delivering the multitasking monkey today for 485,000 won ($447), plus wireless packages that can be purchased in 12- or 14-month installments. "It's really cute," said my 9-year-old friend Stella, a co-worker's daughter who visited CNET's offices today. "I would get one if it was in blue." Parents can also remotely control the 8-inch-tall wheeled robot via mobile phone and, using Wi-Fi, monitor their children (a feature that made Stella a tad apprehensive).

Dawson, a geophysicist with the U.S. Geological Survey in California, said he happened by chance upon the discovery that voice recognition could be applied to seismic data. A visiting researcher from Spain who specialized in voice recognition needed a desk and the USGS just happened to have a spare that she could use. Dawson and Carmen Benítez got to talking one day and decided to apply her skills to decoding data collected from the Norris Geyser Basin.

The North Dakota Army National Guard reportedly deployed an "anti-drone missile system" at the site of the Dakota Access oil pipeline on Tuesday. North Dakota Guard spokesman William Prokopyk confirmed to The Daily Beast the presence of the Avenger missile system. He added that the system was put in place "strictly in the observation role." The Morton County Sheriff's Department echoed Prokpyk's statements, adding that the systems "are used strictly for observation of ungoverned encampments to help protect private property and maintain public safety," according to The Daily Beast. Jon Ziegler, who describes himself as a "citizen journalist," spotted the surface-to-air missile launchers at the site.

Helping employees find the right information when they need it represents a major challenge for businesses. An information worker spends two hours a day just searching for information. Aside from the obvious potential frustration for the employee, there's also real business value at stake here: a recent study finds that employees could be up to 30% more efficient if they were armed with the knowledge needed to get the job done. Cognitive computing has the potential to make real impact here, say Carla O'Dell and Lauren Trees in an article in KM World: They point out that industries as diverse as healthcare, software, financial services and oil and gas exploration are already starting to see results from turning to cognitive technologies. Being able to process massive amounts of data, both structured and unstructured, to provide "personalized, intuitive responses" offers significant promise for the field of knowledge management.

Like most sectors, the solar industry is rapidly embracing ways to analyze and crunch data in order to lower the cost of solar energy and to open up new markets for their technology. The rise of data tools--algorithms, machine learning, sensors--are driving investments in, and acquisitions of, solar startups, while entrepreneurs are launching new companies that are using data to solve various solar industry problems. Meanwhile, big companies are spending money on tracking, monitoring and evaluating data from solar projects worldwide, helping to lower the cost of generating energy from the sun. It shouldn't come as a surprise that the solar sector is the latest to embrace the value of data. Other traditionally non-digital sectors, like the auto industry, oil and gas, and agriculture are turning to managing data as a necessity to keep their technology competitive and their companies in business.