# Edge Computing: A Survey On the Hardware Requirements in the Internet of Things World
## 5 Conclusions and Future Perspectives  
This paper proposes an overview of the main techniques to design hardware platforms able to cope with IoT requirements, by exploiting the Edge Computing paradigm. As it can be observed, many approaches have a clear focus on lowering the power consumption. This is, by now, a basic requirement, since the increasing computational effort affects battery lifetime of many mobile devices. From section to section, all the fundamental components of an IoT electronic system have been analyzed. Despite the general architecture is common to different devices, the input/output part, namely peripherals, is the most variable part. In fact, sensors depend on the type of applications and sometimes the design can be very complex. The main point addressed thought the different sections is that power consumption comes from three main sources: sensor sampling, read and store from and to the memory, transmitting and receiving information. The former is strictly related to the frequency at which data is acquired, and since the power consumption directly depends on the frequency, the faster the system, the larger the energy required. As for memory usage, this represents a huge bottleneck from the power consumption point of view, especially in systems where many accesses are required. Finally, the transmission or the reception of data is a power-hungry task as well, since the intervention of the antenna comes at a non-negligible cost. The Internet of Things era is rapidly evolving toward a scenario where everything is connected and this requires the adoption of new design rules to adapt available technologies to the new challenges. The actual trend suggests that, in the future, IoT will become more and more pervasive, incorporating all the devices around us. However, since it will be impossible to upgrade so many devices in a second moment of their lifetime, one of the IoT paradigm requests is to develop now solutions able to withstand these issues. This is a difficult task also from an economic standpoint, as the processes involved to produce such systems could require selling millions of units in order to cut down the cost for the final user and to make the IoT truly pervasive and accessible. Moreover, Big Data experts must be ready to handle an enormous amount of information never seen before, making Data Mining a fundamental tool. From a hardware point of view, new devices must be able to accommodate the 5G technology, which will invest the entire technological community, bringing the communication to a totally different level from today, thus further widening the range of IoT applications. Hardware must also be aware of another important and very pervasive tool, strictly related to the above mentioned Data Mining, which is Machine Learning. Models such as computer vision, speech recognition and many others are becoming more and more popular, and it is just a matter of time before they will change our everyday life. However, these kinds of algorithms require quite high computing power and, consequently, a substantial amount of energy. This aspect is strictly related to two interesting research fields; on one hand, algorithms must be optimized to meet the hardware and energy constraints dictated by the IoT platforms. On the other hand, researchers need to find new solutions to cope with power requirements of modern devices by working on new battery technologies and more effective energy harvesters. To conclude, the IoT market is very dynamic and constantly evolving, resulting in an extremely appealing field both for manufacturers and inventors. Since it gathers very open-minded people, it represents a good opportunity for emerging technologies to show off their qualities, especially regarding the hardware world. Even though this paper presents many of the main aspects characterizing the IoT world, many other points are untouched.