A Preventive Approach to Weapons Detection for Children Using Quantum Deep Learning

Abstract

AbstractProtection and education is the right of every child. Parents are always concerned about their children’s happiness, education, health, and safety. Protection and security are at the forefront of this list. In today’s world, our young people face several threats, especially the dangerous objects that can be easily accessible at home and in the market. One of the neglected issues in our societies is the access of weapons to children, which results in the loss of precious human lives, including innocent children. In the literature, many techniques have been developed to detect weapons, but the processes are either manual or have very lower accuracy. However, this technique is specifically designed for the safety measures of children. This chapter proposes a technique to handle such a situation. Here, the system watches and alarms when it finds a child with a weapon. Modern technological tools are employed to address this challenge. Deep learning, one of the widely applied domains of Machine learning is designed and trained, to detect weapons with children. At this point, deep learning has proved its efficiency in detecting a child having a weapon. As Quantum Computing has shown unbelievable computing speed, in many complex domains of AI. To cope with future needs, a solution with quantum computing has also been introduced. Quantum Deep Learning (branch of Quantum Artificial Intelligence) solutions have not only proven their impressive performance but also revealed their strength to address future challenges.KeywordsChild protectionDeep learningConvolutional neural networkQuantum computingQuantum AIQuantum deep learningQuantum convolutional neural network