Midgar: Detection of people through computer vision in the Internet of Things scenarios to improve the security in Smart Cities, Smart Towns, and Smart Homes

Abstract

Abstract-Could we use Computer Vision in the Internet of Things for using pictures as sensors? This is the principal hypothesis that we want to resolve. Currently, in order to create safety areas, cities, or homes, people use IP cameras. Nevertheless, this system needs people who watch the camera images, watch the recording after something occurred, or watch when the camera notifies them of any movement. These are the disadvantages. Furthermore, there are many Smart Cities and Smart Homes around the world. This is why we thought of using the idea of the Internet of Things to add a way of automating the use of IP cameras. In our case, we propose the analysis of pictures through Computer Vision to detect people in the analysed pictures. With this analysis, we are able to obtain if these pictures contain people and handle the pictures as if they were sensors with two possible states. Notwithstanding, Computer Vision is a very complicated field. This is why we needed a second hypothesis: Could we work with Computer Vision in the Internet of Things with a good accuracy to automate or semi-automate this kind of events? The demonstration of these hypotheses required a testing over our Computer Vision module to check the possibilities that we have to use this module in a possible real environment with a good accuracy. Our proposal, as a possible solution, is the analysis of entire sequence instead of isolated pictures for using pictures as sensors in the Internet of Things.

The Role of 5G Technologies: Challenges in Smart Cities and Intelligent Transportation Systems

“…Personal and Home Applications is the first category and includes home appliances connected and ubiquitous e-healthcare services which help doctors monitor patients remotely [3,5,11]. Utilities Applications is the second category and includes smart water network monitoring, air quality, video-based surveillance, public safety and emergency services [6,12,13]. The third category is Industrial Applications which usually consists of a network of industrial machinery within a production environment [14].…”

“…Using 5G for urban IoT might provide monitor service of the whole energy consumption in the city, thus enabling authorities to access a detailed and valuable information about energy required by the different public services (e.g., public lighting, traffic lights, surveillance cameras, heating/cooling of public buildings, among others). This will allow identifying the main energy consumption sources and then to plan in order to optimize city energy management [6,12,13].…”

“…In addition to the economic benefit of optimizing energy resources, 5G is expected to help public safety by saving lives through disaster and emergency response or improving crime detection and monitoring. Suspicious baggage in airports, vandalism and criminal identification can be combated by using surveillance cameras and computer vision techniques, as stated in [13]. When the threat is detected, using 5G fast connection, this will be informed to public safety personnel of the status of threats and might help to coordinate response actions.…”

Design and Development of an Internet of Smart Cameras Solution for Complex Event Detection in COVID-19 Risk Behaviour Recognition

“…This led to low-cost and high-accuracy smart monitoring systems for smart home systems [24], security border systems [25], and intelligent traffic information systems [26]. The integration of deep learning (DL) and IoT for automation in detecting and monitoring objects from video streams has been used for person re-identification using multiple cameras [27], disaster management [28], and the detection of individuals in smart surveillance systems [29]. This enables smart cameras to automatically detect objects from various camera streams and then publish them onto an Internet of smart camera (IoSC) network.…”

Distributed Architecture to Integrate Sensor Information: Object Recognition for Smart Cities

“…For example, vehicles need to recognise traffic signals for autonomous driving [4]. Other applications of the detection of objects in cities are the detection of people [5] or the detection of vehicles [6], generally to improve road safety or the comfort of citizens.…”