System for monitoring patients with cognitive disorders comprising: - at least one bed comprising a plurality of weight sensors configured to detect the presence of a patient in the bed ; - a plurality of sensors configured to detect the descending of the patient from the bed ; - a plurality of acoustic sensors able to detect environmental noises near the bed of the patient; - a plurality of flame sensors able to detect smoke and flames near the bed of the patient; - a plurality of shock sensors able to detect sudden movements of the bed ; - at least a wearable sensor placed on the garment of the patient; characterized in comprising: - at least a processing unit , installed at the foot of the bed and housing said sensors configured to detect the descending of the patient from the bed , said acoustic sensors , said flame sensors and said shock sensors , provided with an Internet access and with a control system configured to acquire, digitize and analyze the signals coming from said weight sensors ,said sensors configured to detect the descending of the patient from the bed , said acoustic sensors , said flame sensors , said shock sensors and said wearable sensor through a machine learning algorithm configured to compare said signals with known models and data related to said signals with a database of events recorded during a self-learning phase generating visual and acoustic alarms remotely notified to healthcare professionals provided with mobile devices, minimizing the risk of generating false alarms; - a video camera mounted on the processing unit ; - a computer provided with an Internet access and configured to receive the data transmitted by the at least a processing unit through a wired or a wireless local network. - at least one bed comprising a plurality of weight sensors configured to detect the presence of a patient in the bed ; - a plurality of sensors configured to detect the descending of the patient from the bed ; - a plurality of acoustic sensors able to detect environmental noises near the bed of the patient; - a plurality of flame sensors able to detect smoke and flames near the bed of the patient; - a plurality of shock sensors able to detect sudden movements of the bed ; - at least a wearable sensor placed on the garment of the patient; - at least a processing unit , installed at the foot of the bed and housing said sensors configured to detect the descending of the patient from the bed , said acoustic sensors , said flame sensors and said shock sensors , provided with an Internet access and with a control system configured to acquire, digitize and analyze the signals coming from said weight sensors ,said sensors configured to detect the descending of the patient from the bed , said acoustic sensors , said flame sensors , said shock sensors and said wearable sensor through a machine learning algorithm configured to compare said signals with known models and data related to said signals with a database of events recorded during a self-learning phase generating visual and acoustic alarms remotely notified to healthcare professionals provided with mobile devices, minimizing the risk of generating false alarms; - a video camera mounted on the processing unit ; - a computer provided with an Internet access and configured to receive the data transmitted by the at least a processing unit through a wired or a wireless local network. <EOS>