Internet of Things is rapidly evolving. This thesis includes a study of single-board computers suitable for machine-to-machine communication together with the developing process of a sensor network integrated with a bidirectional communication platform. Raspberry Pi was selected as the single-board computer used in the proposed system. The Message Queuing Telemetry Transport protocol was selected as main communication protocol to handle all exchange of information between the network and the bidirectional communication platform. It was selected because of its reliability, low bandwidth and publish/subscribe architecture. Decision-making procedures were implemented to work with both local sensor data and data from different Message Queuing Telemetry Transport streams, such as GPS data, used to calculate the distance between the user’s smart phone and the office to prepare the workstation, temperature sensors and ambient light sensors controlling Philips HUE light bulbs. The finished sensor network was design to work within office environments to prepare workstations and monitor the work climate. The number of sensors connected to the single-board computer has a major impact in the CPU usage. Measurements and calculations show that 17 connected physical sensors will cause a CPU usage of 96%.