// Method for returning the location/landmark for the mathched hashtag : return type string for landmark that will be matched in the switch statment
static public MatchedLandmark Find_tweeted_landmark(Landmark[] landmarks, string tweet)
{
tweet = tweet.ToLower();
MatchedLandmark found = new MatchedLandmark
{
Landmark = new Landmark()
};
// Searching for each hashtag trigger for every landmark in tweet to find the associated landmark to trigger videos and hooks
foreach (Landmark landmark in landmarks)
{
foreach (string hashtag in landmark.Hashtag_trackers)
{
if (tweet.IndexOf(hashtag) > -1)
{
found = new MatchedLandmark
{
Landmark = landmark,
Hashtag = hashtag
};
break;
}
}
}
return(found);
}
private static void RunTwitterApplication()
{
// BLOCK 1 : Twitter credentials
// Twitter Credentials: Reading in a json configuration file with both credentials for the twitter integration
// and the dedicated twitter account name used for "weather sense"
JObject TwitterConfiguration = JObject.Parse(File.ReadAllText(RootDirectory + @"Package\Config_Interfaces\Twitter_context_profile.json"));
// Locally reading and storing all credential values
string consumer_key = (string)TwitterConfiguration["consumer_key"];
string consumer_secret = (string)TwitterConfiguration["consumer_secret"];
string access_token = (string)TwitterConfiguration["access_token"];
string access_token_secret = (string)TwitterConfiguration["access_token_secret"];
string sensor_account = (string)TwitterConfiguration["sensor_account"];
// Setting twitter credentials
TwitterCredentials.SetCredentials(access_token, access_token_secret, consumer_key, consumer_secret);
// BLOCK 2: Populating Landmarks
// Import excel worksheet for landmark initialization (Name, Categories, Hashtag_trackers, Thematic_Metatags)
// Reading excel worksheet using exceldatareader nuget package
FileStream stream = File.Open(RootDirectory + @"Package\Config_Interfaces\Landmarks_Categories.xlsx", FileMode.Open, FileAccess.Read);
IExcelDataReader excelReader = ExcelReaderFactory.CreateOpenXmlReader(stream);
DataSet result = excelReader.AsDataSet();
// This should initialize all the parameters in the Lanmarks object array using its contructor
int numberoflandmarks = result.Tables[0].Rows.Count - 1;
Landmark[] Landmarks = new Landmark[numberoflandmarks];
for (int i = 0; i < numberoflandmarks; i++)
{
Landmarks[i] = new Landmark(result.Tables[0].Rows[i]);
}
//BLOCK 3: Hook population
// Reading in datatable which contains hooks and their properties
int numberofhooks = result.Tables[1].Rows.Count - 1;
Hook[] Hooks = new Hook[numberofhooks];
for (int i = 0; i < numberofhooks; i++)
{
Hooks[i] = new Hook(result.Tables[1].Rows[i]);
}
////BLOCK 4: Twitter Stream trackers
//// Creating twitter stream for detecting tweets with landmark names
var stream_for_landmark = Stream.CreateFilteredStream();
// Adding trackers for each landmark
foreach (Landmark obj in Landmarks)
{
string[] landmark_hashtags_store = obj.Hashtag_trackers;
// Loop block to assign trackers to each relevant hashtag element in the twitter stream
foreach (string hashtag in landmark_hashtags_store)
{
stream_for_landmark.AddTrack(hashtag);
}
}
//var stream_for_landmark = Stream.CreateFilteredStream();
//stream_for_landmark.AddTrack("volkshotel");
// BLOCK 5: Landing zone and context aware parameters
LandingZone landingzone = new LandingZone();
char MorningOrAfternoon = landingzone.MorningOrAfternoon();
char Weather = Sensors.WeatherSense.SunnyOrCloudy(sensor_account);
//BLOCK 5: Event trigger for tracked tweets
// Event trigger block for each new tweet on the above location based landmark triggers
// String array to store all different weather conditions
// Hook module : Time of the day - categorize as morning, afternoon and evening
// Hook is overlayed on the video - in the center of the video
// Video module : Videos are named as landmark and weather
// Weather detection module : Must read through twitter stream of test account -> Assign a hastag weather -> could filter out the
List <Hook> HooksforExcel = Hooks.ToList <Hook>();
//ExcelFileWriter<Hook> myExcel = new ExcelWrite();
//myExcel.WriteDateToExcel(@"C:\TEMP\myExcel.xls", HooksforExcel, "A1", "D1");
// Landmark is detected by trackers
// Landmark is pushed to method for extracting content from DB
// This can happen either here or in openframeworks
// Once content is extracted it must be sequenced on the basis of :
// Time to play each item : Once one item is played for a certain preset amount of time extract the next from DB
// Time calculation in openframeworks:
// Update loop and draw loop
// The sensing modules exist on this side. So Hooks are selected here and published onto the interface between OF and Encounter#
// Hooks are read by OF and sequenced according to time parameters in OF
//Two kinds of time parameters in OF:
// Amount of time video must be played for
// Amount of time a hook should be shown for
// How does timing fit into the update and draw cycles?
// Use a timer, counting seconds until a value is reached
// Validation for time count can be executed at every loop update
// Update should contain a timing module where all the timing logic can be placed
// Objects required in OF
// OF has to handle video placement, playback and sequencing
// OF has to handle Hook placement, sequencing and timing
// OF has to handle visual blocks with animated elements
Console.WriteLine("Stream detection live now:");
stream_for_landmark.MatchingTweetReceived += (sender, arg) =>
{
// Storing the tweet
string tweet = arg.Tweet.ToString();
// Searching through tweet to find relevant landmark
MatchedLandmark detectedlandmark = Find_tweeted_landmark(Landmarks, tweet);
// We ignore the landmark-specific categories, hooks are categorized by landmark + wildcard humor category.
string[] relevantHookCategories = new string[] { detectedlandmark.Landmark.Name, "humor" }; // detectedlandmark.Landmark.Categories;
// Writing detected landmark to text file interface between here and OF
using (StreamWriter writer = new StreamWriter(RootDirectory + @"Package\Config_Interfaces\TriggeredLandmark.txt", false))
{
writer.Write("{0}\r\n{1}", detectedlandmark.Landmark.Name, detectedlandmark.Hashtag);
}
List <Hook> RelevantHooks = new List <Hook>();
// Selecting hooks that belong to the relevant categories corresponding to the landmark - Obsolete
foreach (string category in relevantHookCategories)
{
RelevantHooks.AddRange((from item in Hooks
where item.category == category
select item).ToArray());
}
// Storing current sensor values
MorningOrAfternoon = landingzone.MorningOrAfternoon();
Weather = Sensors.WeatherSense.SunnyOrCloudy(sensor_account);
// Further filtering hooks based on sensor values
RelevantHooks = (from hook in RelevantHooks
where
(hook.timeofday.Contains(MorningOrAfternoon) || String.IsNullOrEmpty(hook.timeofday)) &&
(hook.weather.Contains(Weather) || String.IsNullOrEmpty(hook.weather))
select hook).ToList();
// Writing the selected hooks to an XML to be read in by OF
using (XmlWriter writer = XmlWriter.Create(RootDirectory + @"of_v0.8.4_vs_release\apps\myApps\OpenEncounters\bin\data\Hooks.xml"))
{
writer.WriteStartDocument();
writer.WriteStartElement("Filtered_hooks");
foreach (var item in RelevantHooks)
{
writer.WriteStartElement("Hook");
writer.WriteElementString("text", item.text);
writer.WriteElementString("category", item.category);
writer.WriteElementString("weather", item.weather);
writer.WriteElementString("timeofday", item.timeofday);
writer.WriteElementString("font", item.font);
writer.WriteEndElement();
}
writer.WriteEndElement();
writer.WriteEndDocument();
}
Console.WriteLine(tweet);
Console.WriteLine();
Console.Write("Landmark Triggered:");
Console.Write(detectedlandmark.Landmark.Name);
Console.WriteLine();
//System.Threading.Thread.Sleep(
//(int)System.TimeSpan.FromSeconds(30).TotalMilliseconds);
};
// Starting twitter stream detection
stream_for_landmark.StartStreamMatchingAllConditions();
}
