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Anesthesiologist plays a role in the recovery of the patient without any risk with the ideal anesthesia management, under the responsibility that the science of anesthesiology is not a preventive, protective, therapeutic method alone.

The practice of anesthesia requires a high level of medical expertise as well as significant practical skill, and most importantly, anesthesia is a team effort. In many cases, the responsibility of not only the expert but also the departments and regulatory authorities that set up the system should be considered. Therefore, the appropriate method for patient safety should often be the systems approach. However, this does not remove the responsibility that each doctor should strive for quality, safe approach and excellence in his work for his patient [1].

Abstract
The objective of this project was to build a system software that could assist any first responder irrespective of their background in first-aid. It employed a combination of Internet of Things (IoT) technologies to dial for emergency medical assistance and make a diagnosis of the treatment needed. An Image Recognition (IR) service was trained using IBM Watson to assess the casualty’s primary condition. Training phrases were fed into Dialogflow to construct a voice and text-based conversational interface for Google Assistant’s Artificial Intelligence (AI) to give a secondary diagnosis. Vuforia’s Augmented Reality (AR) engine in Unity was then enlisted via Target Detection to display a virtual assistant applying first-aid on the casualty. The components were amalgamated using the AI’s autonomous control over the IR and AR applications to create the end-to-end system software. Lastly, XCode, an app-building engine, developed the components into prototype mobile applications. Future prototyping could assist first responders during an actual emergency and complement the Singapore Civil Defence Force’s efforts of promoting high
standards of first-aid.

Keywords: Internet of Things; Augmented Reality; Artificial Intelligence; Deep machine learning; First-aid

Abstract
Perioperative anaphylaxis is a life-threatening systemic allergic reaction. Allergic reactions occurring during anesthesia were found to be between 1/6000-1/20000 in retrospective studies. The mortality rate is between 3-5% [1]. The causes of perioperative anaphylaxis are neuromuscular blocking agents, antibiotics, latex, hypnotic induction agents, chlorhexidine, opioids, and colloids. Risk factors for perioperative anaphylaxis include female gender, mast cell disorders, allergic diseases (asthma, eczema, hay fever), drug allergy, and atopy [2-6]. We aimed to present the anesthetic management in our case who had to have knee replacement surgery, had co-morbidities and had a history of anaphylaxis against multiple drugs.

Keywords: Anaphylaxis; Knee Replacement; Co-morbidities; Anesthesia Management