###### Abstract  
Making the Internet of Things \"green\" has become a major research focus in recent years. The anticipated massive increase in the numbers of sensor and communication devices makes this endeavor even more important, resulting in various solution approaches ranging from energy harvesting to energy efficient routing schemes. In this work, we propose a system that can perform some of the main tasks of the Internet of Things, namely identification and sensing of an indoor moving object, by the means of visible light sensing in combination with off-the-shelf retroreflective foils, without the necessity to place any actively powered components on the object itself. By utilizing the supervised machine learning approach of random forest, we show that these two tasks can be fulfilled with up to 99.96% accuracy. Based on our previous findings in this regard, we propose some advancements and improvements of the overall system, yielding better results in parallel with an increased complexity of the system. Furthermore, we expand the number of performable tasks toward additional movement direction determination. The achieved results demonstrate the applicability of visible light sensing and its potentials for a \"green\" Internet of Things. os 2  
a charging point. The fact that wireless charging suffers from a low charging efficiency is an important issue in such an approach since, although the energy is produced by sustainable energy sources, a huge portion of this energy is lost due to the inefficient charging process. In this work, we propose and demonstrate a different strategy, which, by utilizing the technology of backscattered visible light sensing (VLS), can perform some of the main tasks of an IoT, namely the identification and sensing of an indoor moving object in a passive way. Passive in this regard means that no actively powered components (such as Wi-Fi transmitters or sensors) need to be placed on the object under investigation. This relieves the problem of e-waste as well as the anticipated bandwidth limitations of the RF spectrum [5] as a consequence of the predicted massive increase in communicating IoT devices in the future. Furthermore, the possibility to perform these tasks by means of VLS, whilst the parallel operation of the light source for room lighting remains unaffected, can be seen as another efficiency gain. In recent years, based on the rapid developments in the fields of light-emitting diodes (LEDs), photosensitive devices and associated electronic components, a highly active research field has evolved that utilizes visible light to perform various tasks beyond illumination. Visible light communication (VLC) [6], also known under the abbreviation Li-Fi, is probably the most advanced one among these new applications utilizing the lighting infrastructure. Applications that focus on inferring the position of a user or an object by means of analyzing the impinging light on a photosensitive device are summarized under the term of visible light positioning (VLP). VLP systems can be categorized into active and passive ones [7]. Active means that the user or the object carries a VLP receiver unit, usually consisting of a photosensitive device (e.g., photodiode (PD)), associated electronic circuits (e.g., transimpedance amplifiers) and a processing unit. Passive means that the VLP receiver unit is placed in the infrastructure, e.g., the walls [8], and the floor [9], or it is integrated into the luminaire itself. Approaches where the receiver is collocated next to the light source are also called backscattering systems or non-line-of-sight systems [7]. The line-of-sight in this regard is understood as the straight line between the light source(s) (transmitter) and the photosensitive device(s) (receiver) [7,10]; therefore, non-line-of-sight systems are considered systems in which the light emitted from the light source is not received at the photosensitive device without being reflected at least once.