Smart Predictor for Spontaneous Combustion in Cotton Storages Using Wireless Sensor Network and Machine Learning

Table 3

Limitations of proposed approach features.

Related work	Storage area target	Key advantage	Limitations
[8]	Temperature	RFID- and PSO-based wireless temperature and humidity monitoring technology	Only consider external factors for investigation
[12]	Detection of gases	Propose generation laws of the iconic gas compositions during cotton smoldering.	Study focus did not wait for natural processes that increase cotton heating level for identification of gases, but rather, they give heat from external source to study gases that emerge as a result of heat.
[11]	Temperature	They also did thermal analyses to investigate internal exothermic activity.	Only study temperature and use traditional methods for investigation
[9]	Oxidation temperature	Study self-heating oxidation temperature (SHOT), which, in the current study, is helpful to identify self-heating markers.	The study used traditional instruments for investigation rather than modern technology-based tools/techniques.
[5]	CO levels	Compare combustion characteristics between two processes, i.e., burning and smoldering	Study only focuses on one gas, and there are many other gases that emerge during burning and smoldering.
[10]	Study fire factors	Propose early fire detection by investigation of all such factors and events that contribute to the formation of fire	Only focus on two factors and not directly linked with SC, and also, they use traditional tool for identification of factors.