Temperature and humidity monitoring in warehouses is of utmost importance for the safety of the products during storage. The storage environment has to be calibrated as per the product requirement. The monitoring system should preferably be automated and continuous. Installing a real-time or nearly real-time data recording system is clearly an advantage, even in the smallest facilities. Automated data monitoring provides reliability advantages compared to manual measurements, which rely on human intervention. Because data needs to be recorded accurately and continuously, a cost effective and efficient monitoring platform is also required.
In the recent years, smoke detectors have played an important part in the warehouse fire safety systems along with water sprinklers. Smoke detectors have also proved to be successful in identifying the difference between smoke and dirt hence also having lesser chances of false alarms. The usage of smoke detectors allows us to monitor the concentration levels of the smoke present within a warehouse when installed in proper areas of concern.
The IOT implementation is based on publish-subscribe based protocols i.e. MQTT (Message Queuing Telemetry Transfer). MQTT works on top of TCP/IP protocol was found to be more efficient for implementation and data integrity. Adafruit I/O is a simple to use internet service that follows MQTT protocol to enable IoT devices to GET and POST data using the ESP8266 Wi-Fi module. The global and easy accessibility of the system with the help of cloud platforms like Thingspeak or simple android app can be implemented to achieve the goal of real time monitoring and alert system.
4.2 Block Diagram
Fig.4.1 Block Diagram for Internal Warehouse environment monitoring
4.3 Implementation and Results
4.3.1 Implementation of system in warehouse
The implementation can be seen in two parts. A) Inside the warehouse storage area. B) Inside control and Monitoring Room
• Inside the Warehouse Storage area
As proposed by the project the warehouse storage area has DHT11 Temperature and Humidity Sensor, MQ2 Gas sensor, a Red LED and a buzzer. These components are regulated by the following conditions:
(i)When the smoke concentration of the system detected is greater than the prescribed value, the buzzer starts ringing and the Red LED in the warehouse starts blinking as shown in Fig 4.3, thus warning people to stay away from the area. Also a warning message is sent on the Twilio account.
(ii) When the DHT11 sensor detects the values of temperature and humidity greater than the prescribed value, a warning message is triggered on the Twilio system every time this condition is satisfied.
• Inside the Control Room
The Control room has the ESP8266 Wi-Fi module, the Arduino UNO microcontroller unit, a buzzer and a Red LED and a Green LED.
The components are regulated by the following conditions:
(i) When the smoke concentration is less than the limit set, the Greed LED glows as shown in Fig 4.2 indicating that everything is fine.
(ii) When the smoke concentration exceeds the limit set, the Red LED in the control room glows as shown in Fig 4.3 and the buzzer rings in the cry of warning.
Fig 4.2: Green LED glowing indicating no smoke detected
Fig 4.3: Red LED and Yellow LED glowing indicating smoke is detected
Fig.4.4: Serial Monitor on Arduino UNO
4.3.2 Implementation of system on IoT Platform
A channel is created as shown in Fig 4.5 which displays the data sent through ESP8266 Wi-Fi module from sensors. Each channel has a unique ID, Read API and Write API keys which are used while accessing the channel. This channel acts as the MQTT broker which collects the information from the MQTT publishers i.e the sensors DHT11 and MQ2 gas sensor.
Fig 4.5: Channel Creation on Thingspeak
React is an API which triggers the given request upon meeting certain conditions. In this project, React API is responsible to trigger a ThingHTTP request when the Thingspeak Channel meets a certain condition. Separate conditions are created for temperature, humidity and smoke as shown in Fig 4.6 which are to be set and separate ThingHTTP requests have to be triggered. Fig 4.7 displays the three React conditions for temperature, humidity and smoke concentration.
Fig 4.6: React API on Thingspeak
Fig 4.7: React Settings
Hence the react app here does the following:
Each Time the condition is met, i.e when field 1(Temperature) is greater than the limit set in ℃, the action is carried out as specified in ThingHTTP: Send Temperature
Each Time the condition is met, i.e when field 2 (Humidity) is greater than the limit set in g/m3, the action is carried out as specified in ThingHTTP: Send Humidity
• Smoke Concentration:
Each Time the condition is met, i.e when field 3 (Smoke Concentration) is greater than the limit set in ppm, the action is carried out as specified in ThingHTTP: Send Smoke Concentration
ThingHTTP is responsible for communication among the devices, websites and web services. The request is triggered using React API. Here, ThingHTTP connects the Twilio web account with the channel. Thus the subscriber according to the MQTT approach is the Twilio account user who gets the warning message The ThingHTTP requests used are shown in Fig 4.8 and the settings for temperature are shown in Fig 4.9.Similar settings area done for Send Humidity and Send Smoke Concentration
Fig 4.8 ThingHTTP request
Fig.4.9: ThingHTTP Settings for Send Temperature
The Real time updated values of Temperature (in℃), Humidity (in g/m3) and Smoke Concentration (in ppm) are displayed on the Thingspeak Channel created. Fig 4.10 shows the display.
Fig 4.10: Display of Real-Time monitored values
Twiolio Saas software used for SMS system to trigger a warning message sends the message every time value exceeds the set limit. The message received is shown in Fig 4.11. This message system implemented is the subscriber part of MQTT protocol which is integrated with the help of ThingHTTP.
Fig 4.11: Warning message sent from Twilio account