Thousands of sensors are connected to the Internet and many of these sensors are cameras. The “Internet of
Things” will contain many “things” that are image sensors. This vast network of distributed cameras (i.e. web
cams) will continue to exponentially grow. In this paper we examine simple methods to classify an image from
a web cam as “indoor/outdoor” and having “people/no people” based on simple features. We use four types of
image features to classify an image as indoor/outdoor: color, edge, line, and text. To classify an image as having
people/no people we use HOG and texture features. The features are weighted based on their significance and
combined. A support vector machine is used for classification. Our system with feature weighting and feature
combination yields 95.5% accuracy.